Social Edens Building, mining, and monetizing dynamic online communities
Author Dr. Yoav Intrator, GM Enterprise Architecture, Microsoft Services
Publication Date: May 2013
Acknowledgments The author wants to thank the following people who contributed to, reviewed, and helped improve this white paper: Norm Judah Marc Mercuri George Anderson Marc Ashbrook Jon Tobey Mark Hoffman Yuri Misnik
Introduction Imagine that you’re working in Macau for six months, and your wife has come to visit you. Several weeks before her visit, you joined an online social environment that alerts you whenever any groups in that environment form to alert you of events and topics near you that might interest you, such as Macanese folk-pop concerts, sailing events, and natural disasters. This morning, you left for work just as your wife left to play golf with a friend on Coloane Island to the south. At 9:37 a.m., the building where you work in central Macau starts to shake violently. You run outside and see hundreds of other workers from surrounding buildings. You try several times to call your wife’s smart phone but can’t get through. Then you receive a text message on your smart phone that asks if you want to join a group in the social environment called “Macau earthquake group,” or MEG for short. You click a link on the text message, enter your credentials for the social environment, and see on your smart phone the home page for MEG. It’s fully configured for an emergency and includes a link to the Global Disaster Alert and Coordination System web site (www.gdacs.org) complemented with suggestions about what to do during and after a major earthquake, along with emergency organizations and rescue locations in and near Macau. It displays a button that says, “Tell your family and friends you’re safe.” You press the button and see a pre-written message that says, “I’m OK. How about you?” It shows your current location in latitude and longitude. You recall that when you subscribed to “natural disasters near me” groups in the social environment, you provided a list of contacts such as your wife and children plus their phone numbers to whom you could send such a message. You make minor edits to the message and press “Send.” Other pages linked from MEG’s home page include news feeds from earthquake experts worldwide, text messages from eyewitnesses all over Macau, and even a few photos and video clips of the earthquake from eyewitnesses. Along the bottom of a map of the Macau region, you see scrolling text updates about the quake and feeds from local governmental and volunteer agencies that provide information about shelters and aid services. The continuously updating Macau map on your smart phone Social Edens Building, mining, and monetizing dynamic online communities shows that most of the roads and bridges in Macau and Coloane are damaged. You see short, Twitter-like messages from people who joined MEG, and you send one of your own to say you’re safe outside your building. You also see tweets with hashtags #eqinmacau and #eqinmacauneedhelp that offer links to important resources. Some of your coworkers and Macau friends also joined MEG. You see several of them tagged in the onscreen map of Macau, but you don’t see your wife. After you send her another text message, you’re delighted to see her texting back. She’s OK. She read your “I’m OK” message and your text messages. She’s still near the golf course on Coloane, and she just clicked a link in your ‘I’m OK” message to an invitation to join the Macau earthquake group. A minute later her icon appears on the group’s map.
At 9:57 A.M., you receive a text message that a tsunami is heading toward Macau and will hit the region at about 10:30 A.M. You zoom in on the Macau map on your smart phone, and it shows where the tsunami might reach in various scenarios, from best-case to worst. The golf course on Coloane is inundated in every scenario. Your wife is in the path of imminent death. You text her again and tell her to get out of Coloane or, if she can’t do that, head to high ground. She texts you back that she knows about the tsunami; she received the same message over MEG’s texting environment. She’s trying to get out of Coloane, but if she can’t, she’ll head to a hill just north of the golf course that’s 300 feet above sea level. A text message tells you to head to the hills west of Macau if you can get there. You have no car, but one of your coworkers does, and MEG’s map shows that he’s driving toward the Zhuhai Avenue Bridge on Macau’s west side, which he discovered was open by reading a post on MEG. You text him to pick up you and two other people neither of you know personally but whom you engaged via MEG, and you all agree to rendezvous nearby. You meet there and squeeze into your coworker’s car and drive over the Zhuhai Avenue Bridge and veer south to the Nanyuan hotel. They all clamber out and hike up into the hills above. You stay behind in the rapidly filling hotel parking lot while you follow your wife’s progress on MEG’s map as she and her friend try to flee Coloane. Using MEG, they found a friend who has a car. The map shows that all the bridges north of Coloane are down, and traffic is backed up behind them, so they drive instead toward the Estrada Flor de Lotus Bridge to the west, which the map shows is still open. They then drive west, north, and finally east to the Nanyuan Hotel. You run to her at the back of the parking lot, and as you embrace she apologizes for being late as usual. Then you both hike up the hill. At 10:33 A.M., the tsunami hits. From your perch in the hills west of Macau you watch, terrified, as the tsunami tears through large swathes of the city and surrounding countryside. But you’re safe; the tsunami’s waters don’t even reach the hotel’s parking lot below you. You wonder who among your coworkers survived. After examining Macau’s online maps on the MEG site, you see that all of them are in the hills around you, among the thousands of people who’ve made it to safety here. By 1:00 P.M., the tsunami has receded. MEG’s text messages suggest that aid groups are already responding, and the US Navy is on the way with emergency supplies and help. You and your wife read posts on MEG hour by hour as the horror of the earthquake and tsunami hit home: more than 100,000 people killed and more than $10 billion in damage. Truck convoys bring in food, sleeping blankets, and tents, and helicopters bring in medical supplies for the thousands of people stranded in the hills above Macau. You read about five separate people trapped by earthquake debris who were found by sending text messages to MEG; rescuers geolocated two trapped victims from her text messages. You also read about dozens of people stranded by the tsunami who found rescuers through MEG. The MEG solution saved countless lives today. It was the only functioning real-time information source during the disaster. The thousands of tweets, photos, videos, and personal stories by tsunami survivors that are archived on the MEG make for riveting reading. A month later, its members visit it mostly to reflect on how they survived the disaster. New feeds appear in it to explain how to file insurance claims and how to rebuild damaged buildings and homes. With the help of those posts and your insurance
Page ii Social Edens Building, mining, and monetizing dynamic online communities company, you file a claim for your and your wife’s personal items, which you left back at your hotel before the tsunami. Two months after the earthquake, a Macau newspaper claims that far fewer people would have been killed if earthquake experts had given advance warning of the tsunami. The newspaper hints that this lack of warning was purposeful: Western scientists in league with their governments, it claims, wanted to destroy Macau. Many people in Macau believe the newspaper. You email the newspaper to point out that earthquake experts all over the world warned of a tsunami more than an hour before it hit, but Macau’s infrastructure simply wouldn’t let enough people leave the city in time. The reporter who wrote the story emails you to say, “You’re wrong. Prove it.” You send her and her editor an invitation to join MEG, with its visualization tools for the archived trove of the earthquake and tsunami information, and you send the same invitation to two other major newspapers in Macau. Then you ask selected friends on MEG to send the same invitation to the editors of the top 25 newspapers in the world. The newspaper that published the original story prints a retraction, and the reporter who wrote the story resigns. These events and the resulting news bring a burst of new members to MEG, all seeking to find out what actually happened during the earthquake and tsunami. A reporter at The New York Times uses the group’s trove of information to write a long analysis of what happened during the Macau disaster. It’s reprinted in newspapers around the world, and MEG suddenly gains millions of members.
The technologies for this scenario and others far less dramatic already exist. Social media applications have progressed beyond mere “social” software to become major players in historic events such as the Arab Spring uprisings. This paper lays out a vision of a new kind of social platform that in addition to mining traditional interest-based communities also mines online sources to look for significant events. The platform would invite people to form dynamic online communities that focus on significant events. This system would efficiently monitor, memorialize, mine, and monetize temporal occurrences of any kind, such as sporting events, concerts, political rallies, sales, corporate mergers and acquisitions, centennials, celebrity deaths and births, and more. We call these ad hoc, event-driven communities Social Edens. To retain the interest of a Social Eden’s members, the platform would continuously monitor interactions in the Social Eden and provide members with stimulating, relevant content and tools that match their interests. In addition, a software player could develop the infrastructure to support community-building features that let users or corporations personalize these Social Edens. The software player would gain huge benefits and cachet as the first mover in this space. The player could, for example, commercialize Social Edens with community-targeted services, or mine their content for other collaboration services that no one yet envisions. A player with solutions in news media, social media, and devices could build such a service relatively quickly. Being first to market and achieving deep penetration early would be the keys to success in this endeavor.
Page iii Social Edens Building, mining, and monetizing dynamic online communities Table of contents 1 EXECUTIVE SUMMARY ...... 1 2 MINING STORIES FOR HISTORY ...... 2 3 CREATING COMMUNITIES ...... 8
3.1 TRUST ...... 9 3.1.1 Truthy ...... 10 3.2 COMMON INTERESTS OR PURPOSE ...... 11 3.3 APPLYING THE SOCIAL EDEN PLATFORM TO OTHER DOMAINS ...... 12 3.3.1 Commerce ...... 13 3.3.2 Supply line/infrastructure ...... 13 4 LIFE CYCLE OF A SOCIAL EDEN ...... 14 5 PLAYERS IN THIS SPACE ...... 23
5.1 POTENTIAL PLAYERS IN THIS SPACE ...... 27 5.2 USHAHIDI ...... 27 5.3 SWIFTRIVER ...... 27 5.4 CROWDMAP ...... 28 5.5 FLIPBOARD ...... 28 5.6 ELLERDALE ...... 28 5.7 SOCIAL EDEN PLATFORM DIFFERENTIATORS...... 29 5.8 RELATED SOLUTIONS ...... 29 5.8.1 Microsoft Vine ...... 29 5.8.2 Visualizing.org ...... 30 6 CONCLUSION ...... 31 7 APPENDIX A: RESEARCH ...... 32 8 APPENDIX B: DATA VISUALIZATIONS ...... 39
8.1 VISUALIZATION OF DEFECTIONS IN SYRIA ...... 39 8.2 BREAST CANCER CONVERSATIONS ...... 39 8.3 RECENT SPANISH UPRISINGS ...... 40 8.4 NEWSHOUND ...... 41 8.5 MICROSOFT ACQUISITIONS AND INVESTMENTS ...... 42 8.6 PSYCHOANALYZING THE PRESIDENTIAL DEBATES IN REAL TIME ...... 43 8.7 WAVII ...... 44 9 REFERENCES ...... 46
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1 Executive summary Event-related news and user-generated content are increasingly popular on the web. One-third of the most popular search terms on YouTube are for news events, and 40 percent of news-event content on YouTube is user-generated.1 Real-time, firsthand reports from countless people involved in events are generating a new, personalized view of history—literally a multifaceted one. A major software player has a tremendous opportunity to support this trend by actively identifying significant events and connecting potential audiences to them in communities of interest that we call Social Edens. Such a system would be unique in social media because it would: Offer an extensible model from which to quickly identify and create ad hoc social communities Be event-driven yet support traditional interest-based social communities Build on the growing trend of news content provided by people who are not professional reporters Include impartial, trust-based tools to help people find their own truths about complex events Continuously listen to and feed optimized content to social communities through their life cycles Collect and record historic artifacts in real time to create vast repositories of valuable content Provide marketers with precise micro-targeting tools and opportunities The Social Eden platform could automatically generate ad hoc, event-driven Social Edens or supply the platform with which people or organizations could identify and create their own Social Edens. Once established, a Social Eden would attract members and then continuously engage them by feeding relevant content and tools and by growing and evolving as the event unfolds. The environment would continuously watch and analyze Social Eden members’ sentiments, voting patterns, and chatter and then automatically feed new content that best matches their sentiments. For example, if a Social Eden gathered around a natural disaster, its life cycle might start by guiding people to safety and facilitating emergency aid, then progress to helping Social Eden members rebuild housing and file insurance claims. As the event became less newsworthy, the Social Eden would evolve into the key repository of information about the event. The Social Eden would end its life as a valuable historical archive in which members and other interested parties such as journalists and aid workers could reflect on their experiences on anniversaries of the event. Eden members would vote on the accuracy of the information provided by other members to generate distance-based “clusters of truth” around agreed-upon facts. Members would also vote on the relevance of information feeds from the supporting environment. In addition, the hosting platform would offer powerful, comprehensive features for collaboration among Social Eden members, government agencies, volunteer organizations, non-governmental organizations (NGOs), corporations, and e-commerce companies. The Social Eden platform, services, and content would all be profit centers. By listening to community chatter and news channels, for example, the platform could sense a developing natural disaster and instantiate a Social Eden for insurance professionals to plan for handling new claims. Being the first mover in this area would establish a software company as a leader in social media and entrench its Social Eden system as one of the world’s most valuable repositories of rich-media content, historic information, and marketable data.
1 Pew Research Center’s Project for Excellence in Journalism, “Youtube & News: A New Kind of Visual News,” July 16, 2012
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2 Mining stories for history Until recently, historic events rarely spawned any contemporaneous reporting. Before the printing press, history was oral or handwritten, and it took a long time to compile and distribute historical texts. The first publicly circulated documents were usually authored by governments or churches, which had decidedly one-sided points of view. The Gutenberg bible democratized the Christian religion and helped incite the Protestant Reformation, just like Facebook and other social media helped incite the Arab Spring. The printing press was born in 1440, and the first newspapers followed in1620. Newspapers introduced the concept of reporters—people whose entire profession was to record and report events in an unbiased way. Photojournalism was born in 1850, allowing people to see images of actual events. But until the advent of the telegraph in 1844, the telephone in 1876, the radio in 1897, and the television in 1927, reports in newspapers or letters could take days, weeks, months, or even years to reach the public. The advent of radio and TV cemented the idea of an impersonal version of events by a few select sources to create a single source of truth, which then became known as history. Despite all the technological advances of the last century, this flow of information was stable and one- way: from source to consumer. Figure 1. 16 of top 20 news stores Today, this model is being inverted. In our socially networked in 2011 were event-related world, any event of historic significance is widely reported in a variety of media such as Twitter, Facebook, Google+, and blogs. Events of historic significance are reported in real time by real people; a wealth of information comes from eyewitnesses usually before professional reporters can get to the scene. The recent tsunamis in the Indian Ocean and Japan and the earthquake in Haiti were News events gain more eyeballs recorded in stunning detail by a wealth of “News events are inherently more ephemeral than observers like never before. In five out of 15 other kinds of information, but at any given moment, months between 2011 and early 2012 the most news can outpace even the biggest entertainment searched terms on YouTube were for event- videos.” -Pew Research Center for Excellence in related news stories, and about 40 percent of Journalism the content posted about news events on YouTube was produced by citizens.2 At least 16 of the top 20 news stories in 2011 were event-related. 3 Every modern event generates this rich digital stew of text, film, images, and audio, which provide a much deeper picture of major events than traditional reporting ever could. Rich content creates context. There is vast untapped value in the wealth of information that unpaid observers freely provide. Technology in countless hands creates the perception of truth. As media expert Shelly Palmer wrote, “Marshall McLuhan said, ‘the medium is the message,’ but in the 21st century we say, ‘the median is the
2 Ibid 3 Pew Research Center for People and Press, “2011: Year of Big Stories Both Foreign and Domestic,” Dec. 21, 2011
Page 2 Social Edens Building, mining, and monetizing dynamic online communities message.’ If you are going to report the news, then you are going to have to be able to make the distinction between fact and fiction, truth and narrative, reality and wikiality. The median, the measure of the central tendency, will become the accepted truth — along the same lines as political philosopher John Stuart Mill’s idea of the tyranny of the majority. Television personality Stephen Colbert coined this idea as ‘Wikiality.’”4 Today there is more power in the median than in the media—if we can harness it. Our The median is the message proposed system does just that—harnesses “Marshall McLuhan said, ‘the medium is the message,’ the power of multiple participants and but in the 21st century we say, ‘the median is the observers of an event to help them compile message.’”5 distance-based clusters about it.6 We can -Media expert Shelly Palmer describe any event that people participate in or witness with a tuple: <
4 Ibid 5 Shelly Palmer, “Truthiness in a Connected World, Part 1,” ShellyPalmer Digital Leadership, August 1, 2010 6 For more information about “clusters of truth,” see http://en.wikipedia.org/wiki/Cluster_analysis. 7 Paul Sloan, “In 10 years, folks will share 1,000 times what they do now,” CNET, October 20, 2012
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Global positioning in almost every mobile device will likely ensure that most of the tuples have actual coordinates. Event: This includes an event name followed by (optional) references to a larger, encompassing event, set of events, or synonymous event name. It is common to find multiple redundant names. Examples include: D Day, World War II Tōhoku earthquake London Olympics Nordstrom’s Labor Day Sale Rolling Stones concert Huskies versus Cougars football game Marvel's The Avengers movie Time: Some statements represent specific, bounded time, but others do not, as in these examples: Today After 3: 00 P.M. 2:34 A.M. After sunset During the earthquake June 6, 1944 Within minutes of an event, one could automatically generate a Social Eden that aggregates information about the event, including rich media, and then invite people to spontaneously participate in this Social Eden. Such an environment would gather and collate rich media that is not only nearly instantaneous but could be interactive. Modern cultures have been transformed by people who are eager to share personal, emotional experiences about events, with many eyewitnesses eager to share their truth. Witnesses and those who are engaged with them record, respond to, and discuss their experiences in the shared environment of the Social Eden. Because of the greater credibility of information from first-hand witnesses, the tuple includes a key element: source. The source could refer to either a person or a technology. For example, a technology—a fixed surveillance webcam in Sendai airport—produced the most-watched video of the tsunami in Japan. The future of news and its legitimacy or factual truth is rapidly shifting from professional reporters to communities of non-professional eyewitnesses. This shift can be seen in breaking new stories when no professional reporters, as agents of truth, are yet on the scene of an event. Syndicated news channels often use eyewitness accounts and media streams to provide the first coverage, usually prefacing it with statements such as, “We can’t yet confirm the authenticity of this video.” News channels also hope to become agents of truth by relying on technologies that automatically correlate multiple sources of information and filter out those that do not remotely resemble other reports. Government intelligence systems already use technologies like these to listen to chatter from multiple feeds and correlate them around distance-based clusters that can be mapped and analyzed.8 For example, by using data mapping technologies, multiple reports from different sources in a city about a shooting event will easily cluster around the same area and time: let’s say around 2:00 P.M. on July 11 between 6400 Main Street and 6420 Main Street. The time and place will become more accurate as more and more reports come in and the clusters around the shooting becomes smaller and smaller. As mobile devices with built-in time and location tracking capabilities become ever more common, the reports that people can post to Social Edens would become ever more precise. As Time magazine said
8 Patrick Radden Keefe, “Chatter: Dispatches from the Secret World of Global Eavesdropping,” Random House, February 15, 2005
Page 4 Social Edens Building, mining, and monetizing dynamic online communities recently, “If someone wanted to create a global system for tracking human beings and collecting information about them, it would look a lot like the digital mobile-device network. It knows where you are, and—the more you text, tweet, shop, take pictures and navigate your surroundings using a smart phone—it knows an awful lot about what you’re doing.”9 If the source is hardware such as a trusted camera, the Social Eden would have access to an unbiased source that can further validate time and location in an event.
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Figure 2. Identifying distance-based clusters of truth Although malefactors can use technology to fabricate accounts, the sheer volume of similar content from multiple authenticated and credible sources with little or no contradictory denial content is enough to convince the overwhelming majority of people about the truth of an event. For example, witnesses of the Japanese tsunami spontaneously generated many media assets and made them available on websites in or close to real time. Traditional news channels then rebroadcast these media streams. No one analyzed these media streams for authenticity because it would be almost impossible technically to produce so many similar media streams so quickly from so many different sources. Reports from users of mobile devices who enable location tracking now make it even easier to verify the locations and times of events accurately. Using location tracking technologies, it’s possible to assign different accuracy values to reports that originate from people who are close to or at an event site versus those who report about it secondhand or later. But what if a media asset or its source is faked? For example, what if a source claims that a video clip came from one country when in fact it came from another? In some cases, such fakery might succeed temporarily, but over time a ripple of fake content will always be swept away by a tsunami of real content delivered by authenticated users and devices. An adage says a lie can travel halfway around the world while the truth is putting on its pants, and lies and false rumors fly faster through social media. For example, after an article in the New York Times on May 29, 2012 was misinterpreted, rumors circulated in
9 Massimo Calabresi, “The Phone Knows All” Time magazine, Aug. 27, 2012
Page 5 Social Edens Building, mining, and monetizing dynamic online communities thousands of posts on the Internet that President Obama had added a 17-year old girl to the counterterrorist “kill list.”10 Those rumors turned out to be false. Finding ways to identify and filter out rumors in social media like Twitter has become a challenge for computer researchers.11 Some of their papers have identified how firsthand experience could effectively vote out information that is not credible or relevant and thus minimize the impact of fabrication on history—whether by members of corrupt governments or other malefactors. The Social Eden environment would use a predefined set of heuristics to help Social Eden members and later users such as journalists and historians filter and weigh the credibility of information sources. In their research, Mendoza and his colleagues analyzed hundreds of tweets and retweets that propagated during the Chilean earthquake of 2010.12 Knowing in hindsight which tweets were true, they picked seven tweets that spread confirmed truths and seven that spread false rumors, and they classified those 14 true and false tweets and later tweets and retweets about those tweets into three categories: Affirms: Retweets that affirm tweets or retweets, regardless of whether they’re true or false Denies: Tweets that deny tweets or retweets, regardless of whether they’re true or false Questions: Retweets that seek affirmation of other tweets or retweets
Figure 3. Analysis of true versus false tweets by Mendoza, Poblite, and Castillo As Figure 3 shows, almost 95.5 percent of confirmed-true tweets were affirmed—more than twice as many as false-rumor tweets. False-rumor tweets generated 38 percent denial tweets, while confirmed-truth tweets generated only 0.4 percent denial tweets. More than 17 percent of later tweets about false-rumor tweets questioned them, while only 3.5 percent of later tweets about confirmed-truth tweets questioned them. The Social Eden system could use this crowdsourcing pattern to distinguish false rumors from truth. Combining this heuristic with powerful data visualization tools, Social Eden members could make up their own minds about the truth of postings, and they could filter sources provided by the tuples (people, locations, time, and sources) in addition to Social Eden members’ attributes, such as:
10 Scott Shane, “After Article on ‘Kill List,’ Rumors Fly Fast,” The New York Times, June 5, 2012 11 Eunsoo Seo, Prasant Mohapatra, and Tarek F. Abdelzaher. “Identifying Rumors and their Sources in Social Networks.” University of Illinois at Urbana-Champaign, April 2012. 12 Marcelo Mendoza, Barbara Poblete, and Carlos Castillo, “Twitter Under Crisis: Can we trust what we RT?” 1st Workshop on Social Media Analytics, July 25, 2010.
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Proximity to the event in time and place Proximity in relationship to other observers of the event Ranking of the Social Eden member’s credibility by other credible and authenticated members Authenticated member or device user versus anonymous member or device user The implications of democratized, personalized media streams are profound. Governments can no longer credibly claim to own the truth. Media streams like those generated in the Arab Spring uprisings are helping to topple corrupt governments.13 In places such as Syria, almost the only news sources are local people. Without them and the technologies they use to broadcast their stories and media, atrocious crimes would remain unreported and the truth would disappear, perhaps forever. The Social Eden platform could fill this void by becoming the world’s key repository of filterable, reliable, rich, recorded historical artifacts.
13 Social Capital Blog, “Twitter, Facebook and YouTube’s role in Arab Spring (Middle East uprisings) [Updated 5/232/12],” January 23, 2011
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3 Creating communities Belonging to a community is a psychological state.14 People are much more likely to participate in a virtual community if they can identify similarities with others in the community. Being part of an event gives community members a common identity and purpose, which also creates emotional attachment to the group.15 In the traditional B2B world, this attachment is known as stickiness. While events are fresh, cybersocial stickiness is likely to be very strong, but as the event ages, the social stickiness diminishes if it’s not nourished. The push of the Social Eden can happen in two ways. In the first, the platform will continually Cybersocial stickiness is directly influenced by: listen to and mine blogs, news sites, and social Sense of purpose media to find events of import. These events Right audience will be defined in a heuristic model based on Right content their frequency of hits in a set amount of time Trust and their likelihood to have a significant Technology impact or interest, predefined by an event Time taxonomy. Such listening utilities must first be able to identify potentially newsworthy events and then to distinguish between false rumors and confirmed news. For example, Kate Starbird and Leysia Palen discuss how analysis of tweets and retweets combined with other analysis can be used to identify information that is new.16 When an event of import is established, the model will calculate distances of geography, time, and syntax (vocabulary) between people related to the event, using short distances or common interests to create communities of interest. The platform will then credential people who may be interested (using existing channels such as Facebook and Twitter) to the Social Eden that the platform creates for the event. A second way to establish a Social Eden is to give people or organizations tools with which to set up their own Social Edens and then let them discover and collaborate with other interested people. For example, the Social Eden platform might note growing chatter on an internal B2B communications channel about a certain subject. The platform could then invite interested parties to a new Social Eden to discuss the subject. The Social Eden environment would also gather information to help Social Eden members discuss and solve any issues related to the subject. This capability would give organizations a focused and powerful new learning system with which to anticipate, discuss, and resolve issues before they became problems. An interesting possibility is to create sub-edens for sub-events of larger events. For example, in the 2011 Tōhoku earthquake and tsunami, people with a special interest might want to discuss the Fukushima nuclear power plant meltdown. The platform’s heuristics might discover this as a separate but related event, or the community could set up a sub-eden just as people start sub-boards on a forum. A sub-eden inherits its behavior from its parent Social Eden. At this point, the tuple might seem to be moving from event-driven to interest-driven. However, what brings people together is the event; you went to school with someone, you shared an historic experience, and so on. Even things like insurance purchases are
14 Massimo Bergami and Richard P. Bagozzi, “Self-categorization, affective commitment, and group self-esteem as distinct aspects of social identity in an organization,” British Journal of Social Psychology, December 16, 2000 15 Utpal M. Dholakia, Richard P. Bagozzi, and Lisa Klein Pearol, “A social influence model of consumer participation in network- and small-group-based virtual communities,” International Journal of Research in Marketing 21 (2004) 16 Kate Starbird and Leysia Palen, “(How) Will the Revolution be Retweeted? Information Diffusion and the 2011 Egyptian Uprising,” CSCW ‘12: Computer Supported Cooperative Work, Seattle, WA, February 11-15, 2012
Page 8 Social Edens Building, mining, and monetizing dynamic online communities event-driven; you bought a house, had a baby, got a car, or reached a certain age, all of which changed your insurance requirements.
3.1 Trust Trust and distrust are the basis of social interactions, so it’s only natural that users in Trust versus distrust the cyber social media will look for trust clues “At any given time, the stability of a community and expect cyber tools in virtual environments depends on the right balance of trust and distrust.”17 to help them. We’re also starting to see growth - Alfarez Abdul-Rahman and Stephen Hailes in the population that treats the virtual social world as if it was a physical one. The virtual and physical worlds differ, but people have the full panoply of social needs in both: to trust and be trusted, to give and provide attention, to love and be loved, and so on. Most people, whether in the virtual or physical world, have a fundamental need to determine whether others are trustworthy and credible. Lacking traditional trust clues from the physical world such as facial expressions and tone of voice, cyber social communities try to compensate with a wealth of rich data that is not readily available in the physical world. Unfortunately, this opens the door for some people to assume different personas and pose as others, thus affecting users’ trust.18 Although the virtual world cannot duplicate all the features of the physical world, many computer scientists are working on technologies to enhance trust, security, and the ability to find and feed relevant content in social-networking environments.19 Trust, like truth, is subjective. Establishing truth should be left to the truster, using their own probability filters. The success of the Social Eden platform depends on its members’ ability to achieve the following standards of trust: 1. Trust the environment in multiple forms because: o The environment does not take sides or represent a single truth, but instead lets members find their own truths. o Content that feeds the environment comes from trusted sources. o Users’ privacy is protected. o The environment eliminates software agents that pose as Social Eden members. o The environment is centered on authenticated users. o The provided default trust views are transparent. o Users can self-select different criteria for their views (for example, showing content only from users who were present during an event). 2. Trust or distrust other members because: o Users can demonstrate their credibility and the source of their information (for example, saying “I was there when it happened” and proving it by releasing access to telecom data about their mobile device’s location at the time). o Users can challenge the accuracy of others’ content, thus indirectly challenging their trustworthiness. o Eden members can retract statements that they made and thus try to repair their credibility (for example, changing their own statements that were challenged by others).
17 Alfarez Abdul-Rahman and Stephen Hailes, “Supporting Trust in Virtual Communities,” Department of Computer Science, University College London, January 2000 18 John Seely Brown and Paul Duguid, “The Social Life of Information,” Harvard Business School Publishing, 2002 19 For a review of some of this work, see Appendix A: Related Papers and Technologies.
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o The environment provides access to members’ accuracy ratings from other Social Edens. To enable trust features, the Social Eden platform would use digital agents that we call cyber social agents (CSAs). The Social Eden platform and environment would support CSAs that can: Recognize new events by using CSAs that understand different ontologies and the context of news stories to listen to various news and social channels and cooperatively identify new events. Assess the legitimacy of sources—especially to determine whether a source is human or a machine— to satisfy the Social Eden members’ need to trust the system. Leverage Social Eden member feedback to determine whether content is relevant for a Social Eden. Determine the trustworthiness of members, based on multifaceted analysis of factors such as the time and location of an event compared with information from a member’s mobile device, feedback from other Social Edens about the trustworthiness of that member, and other techniques. Determine what content to feed to the Social Eden based on its life cycle and members’ sentiments. By proximity, assist Social Eden members or groups to identify people with similar stories to their own in other social communities or websites. Identify influencers―people who drive traffic to and within the Social Eden There will always be some who will try to trick the Social Eden system. Given that we are dealing with new technology, techniques to fight this new form of fraud will improve over time. The Social Eden system could mimic the International Olympic Committee and the International Cycling Union, which keep blood samples of athletes on file for many years. Because the Social Eden platform would archive information indefinitely for future forensic historians, Social Eden members and the Social Eden platform could revisit member posts years or even decades later to assess the credibility of members in light of information revealed later.
3.1.1 Truthy An interesting site whose sole function is to analyze trust is Truthy, whose data visualization techniques help viewers understand how memes spread online.20 The site’s name comes from a term invented by television personality Stephen Colbert to describe “claims that feel like they ought to be true, but aren’t necessarily.” By using the site, the Truthy team can identify how political organizations engineer tweets on Twitter to spread misinformation. The team discovered that, for example, it’s relatively easy to determine whether tweets are machine- or human-generated based on their frequency.21
20 Truthy, Indiana University, “Frequently Asked Questions” 21 South by Southwest Conference 2011, “Social Media Data Visualization: Mapping the World’s Conversations”
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Figure 4. Truthy page and user profile
3.2 Common interests or purpose Active participation is what makes communities succeed, and people who participate the most develop influence. Social media expert Mark Silva says that in social media, the reaction of the community is the key to gaining a solid ROI: “return on influence.”22 A joint research project by the University of Arizona and Microsoft in social customer relationship management (CRM) suggests why and how to leverage influencers in forming social communities. The project’s authors concluded that Return on Influence (ROI) influencers have a major impact on the “In social media, the action is the reaction and the ‘I’ level of interest and activity of social in ROI is influence.” – Mark Silva, social media expert communities.23 It identified three pillars of influence: reach, resonance, and relevance. Reach: This is defined by how far an influencer’s information travels across online communities; greater reach means greater influence. Reach as a key performance indicator can be measured by: Popularity: Liking, admiration, or support for an individual or community. Proximity: Position of an individual in a community, which often defines their capacity to influence. Goodwill: The non-tangible value of the influencer. The more goodwill the member or community delivers, the more support they are likely to receive. Resonance: This measures the duration, rate, and level of interactivity around content or conversations and keeps content alive and at top of mind among social media members. Resonance is measured by: Frequency: The rate at which content or conversations materialize on social media. Period: The duration of time the content or conversation is visible after its first appearance. Amplitude: The level of engagement or activity around content or a conversation in a network. Relevance: When users are aligned through subject matter, a series of linked relationships are formed that can quickly send information throughout a community. For example, a user who has a far-reaching
22 Mark Silva, “How Do You Measure Social Media? Return On Influence,” Marketing Daily, Feb 29, 2012 23 George Anderson, Microsoft Services, and Nipa Avlani, Megan Everett, Jennifer Gibson, Joshua Stine, University of Arizona Eller College of Management, “CIO considerations for CRM in a social media world, Part 1,” June 2012
Page 11 Social Edens Building, mining, and monetizing dynamic online communities network connects to like-minded users, each of whom can then influence the communities to which they are linked. To maintain their relevance, influencers must sustain the following qualities: Authority: The influencer has expertise on the subject matter to maintain respect and fan following. Trust: Confidence in an influencer is difficult to measure but generates meaningful relationships. Influencers win the trust of their followers by providing reliable, truthful, and credible information. Affinity: By developing affinity, an influencer boosts his or her position in the community Figure 5. Three pillars of influence in Social Finding influencers before instantiating the Social Eden Media and using them to promote and influence growth in traffic could drive the Social Eden’s success. The platform could use influencers to build common interests or purpose for key classes of Social Edens. In addition, the platform could continuously evaluate new members as potential influencers by measuring their reach, resonance, and relevancy. Then it could incentivize key influencers and solicit their involvement in Social Edens that match their interests and expertise. Once you catch people’s interest for an event, how do you keep them interested after the event ends? How do you maintain interest in an event after it has dropped out of the public eye? There would be a certain amount of momentum created within the Social Eden, especially if people went there and continued to find relevant items there. As people collaborated and developed relationships in the Social Eden, their ties to the community would strengthen, especially if they create or become involved with subcommunities. People who are active in Social Edens would establish additional credentials that strengthen the heuristics that invite them to similar Social Edens or even dissimilar Social Edens if an event was relevant to them. A Social Eden’s stickiness would be important, but so would be its liquidity. Edens should be dynamic so that people could rapidly switch events or topics as the need arises. For example, there might be am interest to establish a Seattle Presidents’ Day Shopping Social Eden with sub-edens for women’s shoes. But shortly after the sale, participants might join a Memorial Day Sale Social Eden, followed by a Labor Day Sale Social Eden, a Black Friday Sale Social Eden, and so on. Although there would be very little need for them to visit Social Edens for past events, the whole or part of the community would move on to events that continue to bind it. A Social Eden should dynamically change into a different Social Eden class to match its members’ interests, so it’s important that the contextual information in the Social Eden could be inherited by a sub- eden or a new Social Eden to keep the new members engaged. Thus the platform should have a mechanism to shift a Social Eden from one class to another so that the platform could support and engage the community.
3.3 Applying the Social Eden platform to other domains Although the original idea for Social Edens revolved around bringing people together for specific events, the same platform could host many similar like-minded communities. For example, governments and NGOs could use the platform to support initiatives. Political groups could use it to support campaigns. A corporation could use the platform for internal communications. Researchers could use the platform to study events in depth. The web services could even be used to create a personal Social Eden that filters online sources and aggregates information about your personal interests. This functionality would go a
Page 12 Social Edens Building, mining, and monetizing dynamic online communities step beyond RSS feeds to bring information from a variety of sources, many of which users would not even be aware of without the platform’s search abilities. And individual feedback would tune the search over time.
3.3.1 Commerce E-commerce would be an easy way to monetize the Social Eden system. The Social Eden developer could mine information from Social Edens and then provide this information as a service to third parties. The developer could also analyze people’s interests to see where they’re going and what communities they’re in. The developer could mine and sell this data while protecting personal privacy. This deep understanding of the customer base would provide precisely targeted marketing opportunities to a single like-minded community and a limited, targeted marketing arena for vendors. The synergy between vendors and a specific community would precisely fulfill that community’s needs, and community members would not have to leave the Social Eden to purchase what they need. Things like transportation, water, food, and funding could all be placed where they’re easily accessible.
3.3.2 Supply line/infrastructure The Social Eden developer could provide an event stream to organizations that would allow them to react to events; for example, rerouting ships to or away from an event, transferring workforces, or balancing computer networks.
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4 Life cycle of a Social Eden A simple analogy to the life cycle of a Social Eden is the life cycle of a teenager’s spontaneous party. Table 1. Life cycle events of a spontaneous party
Event stage Party activity
Preparing A teenager decides to have a spontaneous party and plans it out. Forming The teenager invites his or her friends to the party. Engaging The teenager continuously tries to engage and entertain party guests. Disengaging The guests leave the party. Reflecting and The guests reflect on and share their stories about the party with other guests and analyzing with friends who did not attend. The latter analyze the shared stories to find out what happened at the party.
Regardless of whether events are social parties, epidemics, or natural disasters, they all follow a similar event life cycle. The Social Eden environment will respond to this life cycle. Table 2. Life cycle events of a significant earthquake
Event stage Earthquake Social Eden activity
Preparing Although impending earthquake Like the EPA’s classification, the Social Eden times and magnitudes are impossible event classification will include the earthquake to predict accurately, government event under the natural disaster class. The and local agencies attempt at least to earthquake event class will likely inherit and plan for such events. For example, all add a class of feeds that vary by geography; for the subclasses of what the EPA example, local news channels, local classifies as Natural Events and government emergency feeds, references to Disasters start with preparations.24 An local volunteering sites, mapping tools, and so individual’s level of readiness and on. Government agencies and for-profit and even awareness vary. non-profit organizations can register before events to relevant event classes in specific places and times to provide feeds or to observe in the future. Individuals, too, can preregister for event classes. For example, while registering software products or services, customers could be presented with an offer to join the Social Eden environment and to preregister for specific event classes or collections of classes: “Register me for all newly reported natural disasters or terrorist events in my vicinity.”
24 United States Environmental Protection Agency, “Natural Disasters: Earthquakes”
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Event stage Earthquake Social Eden activity
Forming As the earthquake occurs, the main The Social Eden platform picks up news chatter focus of the local population is about the emerging earthquake and recognizes survival. People will likely use any it as new. It instantiates an instance of the means or tools that can help them earthquake event class and Social Eden, survive, find relatives, shelter, water including default feeds and tools, and it invites and food, and support. pre-registered members, relevant influencers, Coordinating the many volunteer and SMEs to join the Social Eden. groups, local agencies, and Users can now directly engage with the government agencies that respond to environment and with other members in the a disaster is always challenging, but Social Eden. Using the Social Eden, failure to coordinate them can cause government, local agencies, volunteers, and loss of life, valuable resources, and survivors can better collaborate and minimize time. So in parallel, local agencies loss of resources and critical time. and volunteers will likely rush to the Social Eden while attempting to understand the magnitude of the disaster so that they can prioritize their support and then direct services to the appropriate sites and individuals. Engaging While volunteers, local, and The Social Eden environment monitors the government agencies on the ground Social Eden’s members’ sentiments and initially focus on survival, as time provides them with continuous stimuli from passes the focus shifts to recovery relevant feed sources. For example, initial Social and rebuilding, to new efforts and Eden chatter will likely focus on survival, but as individuals engaged with the local time goes on, the Social Eden environment can communities. detect users’ interest in insurance and rebuilding and adjust by providing relevant feeds while soliciting related local businesses to advertise their services in the Social Eden. Eden members can evaluate the accuracy of other members’ statements and respond to them, and they can also vote on the relevancy of the feeds provided to Social Eden members. Current and new influencers are identified and sometimes incentivized to increase their influence. Disengaging The disaster gradually becomes less The Social Eden’s chatter-monitoring tools try newsworthy, so the media, to retain members by continuously providing volunteers, nonprofits, and relevant information to them; meanwhile, it government agencies start to starts redirecting members to other Social disengage. Affected people and Edens that might fit their interests and communities return to daily activities. personas.
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Event stage Earthquake Social Eden activity
Reflecting As the disaster fades into history, The Social Eden’s main focus now is to support many members start to reflect on its members in analyzing distance-based their experience and share it with clusters. Because the Social Eden platform others. Members may have wildly recorded the Social Eden’s chatter and feeds, varying memories of the disaster, and the Social Eden is useful now as a way to different truths emerge. Some discuss and analyze what happened during and people, like holocaust deniers, are after the disaster. Its visual analytical tools, disaster deniers. On the disaster’s which were available earlier in its life cycle, are anniversary, historians and the media now the main focus of members. They can use will likely try to contact members to these tools to filter reports from people who discuss the disaster. were actually present during the disaster and check their recorded stories and multimedia artifacts against hearsay stories or any newly discovered content to see how well they match the Social Eden’s distance-based clusters for the disaster. To increase Social Eden traffic, just as in the engaging stage, relevant influencers such as famous historians are incentivized to join.
The following subsections describe in more detail the functionality of a Social Eden during its life cycle. Preparing A set of event classes with default behavior (functionality) is in place. The classes are based on ontologies that support different domains. For example, the Environmental Protection Agency uses a natural disaster ontology that includes drought, earthquakes, extreme heat, flooding, and so on.25 The Biocaster biomedical ontology developed in Japan, illustrated below, helps epidemiologists detect and track outbreaks of infectious diseases by monitoring hundreds of Internet news feeds simultaneously.26
25 United States Environmental Protection Agency. “Natural Disasters.” 26 Ai Kawazoe, Hutchatai Chanlekha, Mika Shigematsu, and Nigel Collier, “Structuring an event ontology for disease outbreak detection,” BMC Bioinformatics, Apr 11, 2008
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Figure 6: Biocaster ontology The structure of the Biocaster ontology, illustrated in the following figures, includes (on the left) a high- level taxonomy of events, and (on the right) detailed classes (causes, includes, hasAgent, hasTheme) with links to multilingual synonyms.
Figure 7. High-level taxonomy of events Figure 8. Detailed classes
Similar classes in the Social Eden platform will include rules for instantiation, including default news feeds, business sponsorships, functional tools, and so on. Businesses, local agencies, and governments can preregister for an event class based on time, location, participants, and other business rules. Marketing and B2B deals could be done in advance and provide precisely calibrated advertising opportunities. Businesses such as AccuWeather.com might preregister to provide weather services during future flu outbreaks in North America while Yahoo.co.jp might preregister to provide weather services during future flu outbreaks in Japan. Or they could specify that they would advertise on a Social Eden for a sporting event or concert, but only if it coincides with a snowstorm. During this stage, target influencers including SMEs can be identified and potentially incentivized to agree to be included when relevant Social Edens
Page 17 Social Edens Building, mining, and monetizing dynamic online communities are instantiated. Each of the classes could be instantiated at any time (triggered by the platform listening to emerging news) or at scheduled times (as with a scheduled large concert).
Forming The Social Eden platform constantly listens to news and media chatter and then maps incoming news items to pre-defined event classes, such as terrorism, crimes, epidemics, sales, artistic and sports events, etc. Firsthand media assets have an untapped value that secondhand media assets do not have. We propose a platform that includes configurable searches targeted to the news and social community outlets. This platform would scan for locally and globally significant events and then, in addition to inviting preregistered individuals, dynamically solicit (directly and indirectly) potentially interested individuals or communities to a newly generated Social Eden that collects relevant information about that event and facilitates collaboration among its members. If an event is new (that is, no Social Eden has been created for it yet) and its sources are evaluated as trustworthy, the platform would create an instance of an applicable Social Eden class. Social Eden classes would include a default set of related news feeds and even a set of predefined members. For example, a shooting event would instantiate from a predefined Shooting class and include links to local government agencies and news channels. As news about the event is clarified, the event class might change to Terrorism to reflect updated news feeds. The following figure illustrates the solicitation of new members to Social Edens based on Bing news events.
Figure 9. Solicitation of new members to Social Edens based on Bing news events Pre-identified influencers (as promoters or SMEs) are requested to join the Social Eden. Users who register to be invited to such a Social Eden if the events happen in their neighborhood, close to their travel location, or where other family and friends reside are automatically invited to join the newly created Social Eden. This Social Eden automatically receives relevant news feeds. In some cases, government agencies will likely provide content to the Social Eden. The Social Eden continuously seeks other members by advertising itself; for example, by posting on Facebook, advertising on news channels, and so on. Before anyone can join a newly instantiated Social Eden, individuals or organizations must classify their relationship to the event and thus their credibility by choosing proximity categories such as: I am/was at the event (A category provided if the person’s location-based device cannot confirm that the person was present) I am/was a witness of the event
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I know someone who is/was at the event (additional questions about the relationship might be solicited) I heard about the event
Engaging The environment will continuously and automatically analyze the Social Eden’s chatter and determine what information to feed to the Social Eden. Similar to the Like button in many social computing environments, Social Eden members can use an Irrelevant button to help the environment optimize feeds and other sources of information. Members can also press the Irrelevant button to critique an information feed. (The Irrelevant button concerns the relevancy only of automated feeds, not member posts.) Over time, this learning system will improve the quality of the automated feeds and help the environment learn so that it will, for example, avoid feeding the Social Eden news stories about turkey, the bird, when Social Eden members are concerned about Turkey, the country. (This snafu was seen recently in Google International News.)
Figure 10. Google News misplaces a story about turkey in a feed about Turkey, the country Users can vote on the accuracy of other Social Eden members’ postings similar to how other social media sites solicit feedback on content by assigning the post one to five OK signs. Any vote of less than five OKs will trigger a dialog to solicit feedback, such as “Please identify any inaccuracies in the post.” This rating is directed at a single post, but it affects the member’s overall accuracy rating. The environment continuously monitors the influence of members. Members can chat and discuss the event in the Social Eden and enjoy Social Eden support from various channels. For example, a Social Eden built around a Lord & Taylor sales event is likely to gain support from the Lord & Taylor sales group, which would answer members’ questions.
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As technology has grown to allow innumerable data feeds about any event, it also has provided the tools to sort through this information. It is quite possible to crawl through other news and social media sites to record and match tuples such as << person, location, event, time>, source> with existing ones. With such tools, the platform could sift through countless sites and find specific new details and potentially new members. Then the platform could invite these people to join the Social Eden. Many major software companies already have large databases of potential community members, with enough information about them to filter and propose communities for them to join. For example, imagine that there is a shooting in central Los Angeles. The event is identified and mapped to an event-related taxonomy (a Shooting class would have subclasses such as Terrorist, Gang, Fireworks, and so on) or a folksonomy (which users define by tagging). Although it is not yet clear how best to classify the shooting, all options get similar probabilities and a set of common instructions are pulled to determine how to react to the event and who potentially to solicit. The platform could specify a radius of one mile around the shooting and use mobile location identifiers (and allow people to opt out via email) to identify people who live in this vicinity. Then the platform would build a Social Eden and channel all relevant news about the shooting from traditional news channels. As more information is gathered from the information river, better classification and more accurate actions are possible. If chatter suggests that the shooting is gang-related, the platform will provide the Social Eden with feeds on historical gang activities in this vicinity. If chatter suggests it’s a terrorist activity, the platform could notify members of government agencies and invite them to participate. In another illustration, consider the recording of Hillary Clinton’s 1996 visit to Bosnia to visit U.S. troops on a peacekeeping mission and her later misstatement in 2008 when she was a Democratic presidential candidate that she had faced sniper fire on that trip, or watching the video that shows presidential candidate Mitt Romney at a campaign fundraising event in Florida talking about “the 47 percent of Americans who pay no income tax.” Imagine being able to solicit viewers to a Social Eden to discuss these topics, perhaps with Social Eden members who claim they were there at the events as they happened.
Figure 11. Joining a Social Eden based on a news event
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All of the provided content can be complemented with a truth index to determine the probability that it is true. For example, if initial reports identify two adjacent streets where the shooting happened, the level of confidence in the street name will vary until reports that identify the right street become significantly more reliable. The platform would recentralize this sea of information in a single location and leverage all the power of social networks, but at the same time it would create new ones. For example, people outside the event would have multiple avenues to look for loved ones or find information that would have been too difficult or unimportant to track in previous models. Using such a site and its built-in tools, people could ask for and receive aid from a vast array of sources never available before. Social Edens don’t have to involve just disasters or past events. There are many other times when people come together and could use similar information for planned or expected events. Such events might be campaign events, protest gatherings, concerts and festivals, sporting events, TV shows, corporate mergers and acquisitions, and so on. (Microsoft, among other companies, explored something similar with its TownHall system, a cloud-based political engagement platform.27 Other companies have developed social platforms for TV shows, movies, and sporting events, such as the social site and iPad app GetGlue.28) The Social Eden platform could also be adapted in portals for commercial sales and corporate events. It would allow users to evaluate the event’s credibility by viewing historical rankings of the event’s community and comparing the event to similar events. The environment has advanced data-curation features so that its data is permanently preserved and easy to re-use. The environment also has state-of-the-art data-visualization features to make mining and presenting its data intuitive. These data-curation and visualization features would be immensely valuable after an event happens. These features would compile and preserve the history of an event from dozens, hundreds, or even thousands of individual viewpoints, just as software like Microsoft Photosynth can stitch together hundreds of user-submitted photos into a comprehensive, temporal tableau of a significant event from a photo that has great value as an historical artifact.29 New social-media products would be integral tools in many classes of Social Edens. The environment would also provide powerful filtering tools. For example, later users could select narratives only by people who were present at the event, as confirmed by location-based services. Just as the platform supports Social Edens with an appropriate set of channels, the platform will include different default tools for different classes. For example, Social Edens that concentrate on financial events such as corporate mergers and acquisitions might provide Bloomberg News, while foreign exchange Social Edens would use financial-analysis tools such as currency conversion calculators, and Social Edens that deal with temporal news events might include tools for editing and archiving photos, audio, and video.
Disengaging This stage is less a process than a state when Social Eden members’ interest wanes as the event becomes history. Regardless of the event, the system could then solicit members to participate in Social Edens that better match their interests.
Reflecting and/or analyzing Like the preceding stage, this stage is less a process than a state that reflects a renewed interest in the event. For example, an anniversary of the event will bring old and new members to the Social Eden, with
27 Microsoft, “Introducing Microsoft TownHall,” April 19, 2010 28 Dan Milano, “GetGlue HD Simplifies Finding What’s On TV,” ABC News Technology Review, August 16, 2012 29 See, for example, the tableau of Washington, D.C. on January 20, 2009, when Barack Obama was inaugurated: http://photosynth.net/view.aspx?cid=05dc1585-dc53-4f2c-bfb1-4da8d5915256
Page 21 Social Edens Building, mining, and monetizing dynamic online communities old members reflecting on their past stories and experiences and new members analyzing what happened. In such cases, the Social Eden will prioritize certain analytical and visualization tools over others either in advance (on a known anniversary) or through another trigger (a spike in new membership). Over time, the site will become a historical artifact and likely will gain the interest of historians, students, and others who wish to have a better insight into what happened during and after the events. Visualization tools with interactive filtering and data mining will enable the formation of clusters of truth. The site will represent an interactive historical record that will be of immense value to future historians, who will likely have forensic data skills. Just as Photosynth and other photo-editing software can stitch together many photos into a single rich visual tableau with depth and breadth, why couldn’t one stitch together multiple stories into a unified “storysynth” that has the broad perspective of a Social Eden community and the depth of historical evidence? To enable this vision, we must figure out how to stitch together an e-chronology of multiple sources. This idea goes back to the Defense Advanced Research Projects Agency’s shelved project LifeLog, which was canceled in 2004 for privacy reasons and because of public pressure.30 This project focused on chronologically recording an individual’s experiences and making them available at a later time. With multiple mobile devices recording individual locations, shopping system logs, street surveillance cameras, and now the Google Glasses project, this vision is close to reality. In the near future, technology will be able to stitch together and summarize objective data from multiple individuals to form historical records of events. As in the Engaging stage, the platform will attempt to optimize the Social Eden’s Developing a Storysynth feature chatter, and over time the process will repeat through Disengaging, followed by Just as Photosynth can stitch together many photos Reflecting or Analyzing. into a single highly rich visual medium with depth and breadth, why can’t we stitch together multiple stories The Social Eden system should listen to into a unified history—a Storysynth? different types of social media and understand the socio-demographic breakdown of each type because they might have different political and social sentiments. A recent analysis of conversations on Twitter, Facebook, and blogs about the first 2012 presidential debate, for example, found that Twitter users (by 35 percent to 22 percent) and Facebook users (by 40 percent to 36 percent) believed that Barack Obama won the debate, but a large majority of bloggers (45 percent to 12 percent) believed Mitt Romney won the debate.31
30 Noah Shachtman, “Pentagon Kills LifeLog Project,” Wired, February 4, 2004 31 Pew Research Center’s Project for Excellence in Journalism, “Social Media Debate Sentiment Less Critical of Obama Than Polls and Press Are,” October 5, 2012
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5 Players in this space The proposed Social Edens system would be unique, but players with similar capabilities might emerge from two sectors: Online news media such as CNN with iReport, FOXNews with uReport, and the Wall Street Journal with WSJ Social, which promote user-generated news sourcing and user interactions with news stories. Social media platforms such as Facebook, Twitter Google+, Tumblr, YouTube, Vimeo, MySpace, Yammer, and others that are based on user-generated content. As traditional news media lose subscribers, they are driving to expand their reach into social media. In 2009, FOXNews and MySpace―both of which were owned at the time by Rupert Murdoch’s News Corporation―partnered to launch Fox’s social media platform uReporter. (News Corporation divested itself of MySpace in June 2011.) The Wall Street Journal also partnered with Facebook to give readers the ability to read WSJ articles in Facebook. To do so, users have to let WSJ access their Facebook profiles and post on users’ walls. WSJ Social provides a curtain of news experience where users read comments and share articles with friends.32 Companies in the United States and China will likely have the Figure 12. Survey information about biggest impact in this space. User-generated news content is receiving news via social media especially popular in China, where in the absence of an independent and free media, citizen journalism and social media are thriving. China has more than 500 million Internet users and the world’s most active social media users.33 Since 2010, Internet users in China have produced more content than professional websites.34 Just one Chinese user-generated video site— Tudou, which is known as the YouTube of China—had more than 225 million unique visitors in December 2011.35 News of China’s massive Sichuan earthquake in 2008, for example, was first reported on Sina Weibo, China’s version of Twitter. Chinese citizen journalists posted maps of the quake and accounts of shaking buildings and evacuated offices. What’s more, in a rare moment of openness under the Communist government, citizen journalists were also able to investigate and critique officials’ handling of the disaster.36 This openness was in stark contrast to government information about the earthquake in Tangshan 32 years ago, “when the Chinese government refused for months to admit the 7.8 magnitude earthquake had even happened, despite the deaths of an estimated 240,000 people.” 37
32 David Cohen, “Wall Street Journal Unveils Facebook Edition, WSJ Social,” AllFacebook, September 20, 2011 33 Cindy Chiu, Davis Lin, and Ari Silverman, “China’s social-media boom,” McKinsey & Company, April 2012 34 Qiang Xiaoji, “User-generated content online now 50.7% of total,” China Daily, July 23, 2010 35 Tudou, “About Tudou” 36 Joyce Nip, “Chapter 7: Citizen Journalism in China: The Case of the Wenchuan Earthquake,” Citizen Journalism: Global Perspectives 37 Malcolm Moore, “China earthquake brings out citizen journalists,” The Telegraph, May 12, 2008
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Two other major stories in China were broken by citizen journalists. Posts by an environmental blogger, Ma Jun, about conditions at Apple’s Chinese manufacturing plants forced Apple to reconsider pollution and labor standards in its supply chain. Another environmental blogger, Liu Fatang, posted 40 articles on his blog about how Chinese developers had destroyed one of the world’s last groves of water coconut trees to make space for a yacht marina. His stories won him the citizen journalism prize at the Chinese Environmental Press Awards. Boxun.com, an overseas Chinese user-generated content community, is the first known Chinese website in the model of citizen journalism. It may also be the first Chinese blog, having started in 2001. Boxun covers international political news and human rights abuses in the People’s Republic of China. It allows anyone to submit news to the site. Editors attempt to confirm and verify the articles, with pictures and videos published for evidence. Readers include NGOs and government organizations Figure 13. Social media is not yet an seeking information about China.38 overwhelming driver of news In China, sites such as Sina Weibo (with more than 330 million users in China) and Renren (often called China’s Facebook, with more than 147 million mostly college-educated users) is driving social networking. Sina Weibo tells readers exactly what other readers care about every day. Recently, the key word Shifang was among the top ten most talked-about subjects. Shifang is a city in southwest China where mass protests broke out against the building of a copper alloy plant. The protest escalated when police not only used tear gas but also stun grenades on the crowd.39 “An anonymous Chinese blogger called Bloody Map has collated incidents of illegal land grabs and property demolitions and plotted them on Google Maps…. There are actually two Bloody Maps: a “revised” version edited by the founder that shows only cases reported by media, and an “open” version that anyone can add to or edit.”40 In another case of citizen journalism in China, a letter posted on the Internet by 400 parents of children working as slaves in brickyards Figure 14. Social network users in China 2011-2014 triggered the national press to finally report on the scandal, which some rights groups say had been going on for years. The parents’ Internet posting was part of a growing phenomenon for marginalized people in China who cannot otherwise have their complaints addressed by the traditional, government-controlled press.41
38 Wikipedia, “Boxun.com” 39 Al Jazeera Staff, “Chinese citizen journalism succeeds,” Al Jazeera, July 5, 2012 40 Colin Shek, “Social media and citizen journalism help chart China’s violent land grabs,” Journalism.co.uk, November 9th, 2010 41 ABC News, “’Citizen journalism’ battles the Chinese censors,” Jun 26, 2007
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“China’s online news video market could be one of the few ‘blue oceans’ left for Internet portals,” says Li Ya, COO of Phoenix New Media Ltd, the country’s fourth largest Web portal by audience viewing. User- generated content will play a big role in future news websites, Li says.42 Social media has a much greater influence on purchasing decisions in China than elsewhere because Chinese are much more wary of news and advertising than citizens of Western countries and thus rely far more on recommendations from family, friends, and trusted acquaintances. A recent Pew Research Center article demonstrates the growing relationship between the news media and social networks. It shows that although public trust in the news media is eroding, they are still more trusted than other news channels. This information helps explain why social media will seek to increase users trust in their content while news media will attempt to gain access to more captive audiences in the social media.43 We predict that that over time, through acquisitions and imitation, traditional news and social media will converge. Many software companies already have online news capabilities. By combining such capabilities with mobile technology and devices, this model could be a winning strategy for a large software company. Pew Research Center’s Project for Excellence in Journalism assesses that among the many social channels, Facebook and Twitter will dominate this crossing between social media and the news media. Although clearly growing, the population that uses these social networks for news is still relatively small, especially those who do this very often. Most of the news media in the US obtained part of their traffic from Facebook. And last year Figure 15. Symbiosis of social media and traditional media Facebook introduced Social Reader, which lets users interact with online news without leaving their site. The entrenchment of social media giants such as Twitter and Facebook might make it look Traditional news vs. social media news difficult to get into the social media space. But “You can’t rely on users coming to you anymore. (WSJ the explosive growth of Google+ against its is) navigating the content within the app around competitors proves that new sites that are people, (making) every user an editor.” properly positioned can gain astonishing -Maya Baratz, head of new products at the Wall Street numbers almost overnight. According to tech Journal.44 blogger Akar Anil, “Twitter got 10 million users in 780 days (2.13 years), Facebook got 10 million users in 852 days (2.33 years) whereas Google+ gained 10 million users just in 16 days (2 weeks).
42 Wikipedia, “Internet in China” 43 Pew Research Center for the People & the Press, “Press Widely Criticized, But Trusted More than Other Information Sources,” September 22, 2011 44 Megan Garber, “With WSJ Social, the Wall Street Journal is rethinking distribution of its content…on Facebook,” Nieman Journalism Lab, September 20, 2011
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Google+ is growing exponentially and becoming popular among users.” 45 Google+ has since grown to at least 110 million users, although its growth is slowing and many Google+ users rarely visit it.46
Figure 16. Growth of Google+, Twitter, and Facebook This figure shows that today, entry barriers are relatively low and that catching up to competitors is relatively easy if you have an interesting value proposition. We daresay that the attraction of such sites is the cool factor. Similarly, because barriers might be very low for competitors to catch up, the competition is keen. From a user’s perspective the barriers to enter these communities are also low, so people shift from one application to another as applications arise to suit a need or the alternative becomes more popular. But as we have seen with MySpace, the cool factor is not sustainable and millions of users can shift to the next cool site because of a lack of true value-added services. MySpace lost millions of members who migrated to Facebook, most of them following the new cool factor and newly available value propositions. Because of the ease of both implementation and changing from one application to another, social media applications have to appeal over time and evolve to match community interest. The dynamic nature of communities also defines evolution in the Social Eden’s value proposition. Facebook recently gained its billionth user.47 But Facebook’s stock valuation melted down partly because investors grasped the relatively low barriers to entry into the social media space. The Facebook stock situation begs the question: What keeps people tied to a particular social networking platform besides a lack of data portability? It also begs a corollary question: How can we increase the value proposition and stickiness of a platform? Surprisingly, many social networking sites connect people much less loosely than their predecessors such as Usenet, Classmates.com, or even LinkedIn. Most of the earlier implementations worked with people who were more tightly bound to common interests or who shared an experience such as going to school or working together. But with Facebook, clustering is almost exclusively among loosely organized social groups. You may share friends with overlapping general interests, but there is no safe area to collaborate with like-minded people whose judgment you trust
45 Aakar Anil, “Growth of Google Plus Vs Twitter Vs Facebook; Google+ Got 10 Million Users Just in 16 Days,” Buzzom, July 22nd, 2011 46 Chris Crum, “It Looks Like Google+ Growth Is Doing Pretty Well Globally Too,” WebProNews, July 26, 2012 47 Associated Press, “Mark Zuckerberg crows on his personal page as Facebook surpasses one billion users,” October 4, 2012
Page 26 Social Edens Building, mining, and monetizing dynamic online communities based on the context. On Twitter, you follow people because you care what they think. In both of these newer platforms, networks of individuals are not as closely bound by common experiences.
5.1 Potential players in this space Several small software players already have many or most of the capabilities needed to create a Social Edens system. These small players include Ushahidi, Swiftriver, Crowdmap, Flipboard, and Ellerdale.
5.2 Ushahidi Ushahidi, the site that most closely matches the Social Edens concept, is an open-source crowdsourcing site that provides a platform for people to quickly set up a page to aggregate news reports. Ushahidi has made great inroads in crowdsourcing,48 from monitoring elections to the Tōhoku earthquake and tsunami to “snowmaggedon”49 events in urban settings. It has a comprehensive set of web services to manage information and people. The first Ushahidi site was put together in just a few days. Its website states: “We build tools for democratizing information, increasing transparency and lowering the barriers for individuals to share their stories. We’re a disruptive organization that is willing to take risks in the pursuit of changing the traditional way that information flows…Our roots are in the collaboration of Kenyan citizen journalists during a time of crisis.” Ushahidi, which means testimony in Swahili, was initially developed to map reports of violence in Kenya and peace efforts after the post-election fallout at Figure 17. Ushahidi the beginning of 2008, based on reports submitted via the web and mobile phones. Since then, the name Ushahidi has come to represent the people behind the Ushahidi platform. This website had 45,000 users in Kenya, and as the site says, “was the catalyst for us realizing there was a need for a platform based on it, which could be used by others around the world.”50 5.3 Swiftriver Ushahidi includes Swiftriver, “a free and open source platform for helping people to make sense of large amounts of information in a short amount of time. It is a mission to democratize access to the tools used
48 Jeff Howe, “The Rise of Crowdsourcing,” Wired, June 2006 49 Lloyd Alter, “Open-sourced, Crowd-sourced Ushahidi Platform Following Snowmageddon,” Treehugger, December 28, 2010 50 Ushahidi “About Us”
Page 27 Social Edens Building, mining, and monetizing dynamic online communities to make sense of data - discover information that is authentic, accurate and above all, relevant - by providing the following capabilities: Gathering and filtering of information from a variety of channels; e.g. RSS, Email, SMS, Twitter, etc. Drawing insights from the collected information Allowing people to create buckets of information using their own expectations of authority and accuracy as opposed to popularity”51 5.4 Crowdmap Crowdmap (https://crowdmap.com) “designed and built by the people behind Ushahidi, a platform that was originally built to crowdsource crisis information. As the platform has evolved, so have its uses. Crowdmap allows you to set up your own map of Ushahidi without having to install it on your own web server.”52 Crowdmap includes: Interactive map. One of the most powerful ways to visualize information is via a map. Choose a location and start plotting reports, information, and other data right away. Dynamic timeline. Track your reports on the map and over time. You can filter your data by time and then see when things happened and where, as it’s also tied to the map. Real-time data tracking. The admin area of Crowdmap has analytical tools for you to make sense of your incoming data in real time. 5.5 Flipboard Flipboard (www.flipboard.com) is ”your social magazine built for a mobile world. By showcasing social media and Web content in a print-style magazine, it’s one place to enjoy and share all of your news and life’s great moments.”53 The Flipboard application works on Apple’s iPad, iPhone, and iPod Touch, Android devices, Kindle Fire, and Nook. The application collects the content of social networks and other websites and presents them in magazine format on the device. The application is designed for touch screens and lets users flip through their social networking feeds and feeds from websites that have partnered with Flipboard. 5.6 Ellerdale Ellerdale (http://flipboard.com/press/flipboard-acquires-ellerdale), “founded in 2008, developed a web intelligence technology that applies semantic analysis to large, real-time data streams to extract relevant and valuable information. To date, Ellerdale has indexed more than 6 billion messages from around the social web and currently processes nearly 70 million messages per day. This technology and data set will be become the relevancy engine for the next release of Flipboard, which will enhance the reader’s experience by always surfacing the most important and personally interesting information from Facebook, Twitter, and other social networks. Designed from the ground up for iPad, Flipboard creates a magazine out of a user’s social content. With Ellerdaleʼs technology, future versions of Flipboard will be able to extract, categorize, and feature highly relevant and hot trending content from across a variety of social networks.”54
51 Ushahidi, “SwiftRiver – Community Wiki – Ushahidi” 52 Crowdmap home page, “Crowdmap | Create and Share Interactive Maps Online” 53 Flipboard, “Flipboard Community” 54 Flipboard, “Flipboard Acquires Ellerdale to Boost Content Relevancy in New Social Magazine” July 21, 2010
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5.7 Social Eden platform differentiators The Social Eden platform would be different from other social media sites because it would: Offer an extensible model from which to quickly identify and create ad hoc social communities. It uses a push model that brings together people who have shared interests and facilitates collaboration among the shared tuple: <
5.8.1 Microsoft Vine The Microsoft Vine service was intended to let people keep in touch with each other during emergencies. As one article headlined it, 55 “Microsoft Vine is Twitter for Emergencies.” Figure 18. Microsoft Vine dashboard and alert
55 Stan Schroeder, “Microsoft Vine is Twitter for Emergencies,” Mashable, April 28, 2009
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Vine was released in beta only, and was a desktop-only application that ran on Windows XP SP2 and Windows Vista. Vine was inspired by the confusion after Hurricane Katrina, although Microsoft pointed out that people could use it to get help with childcare, connect with neighbors, report last-minute changes in events, and more.56 Microsoft discontinued the Vine service in 2010.
5.8.2 Visualizing.org The ability to visualize social data is critical to the success of the Social Eden platform. Such visualizations must enable contextual navigation—letting members, for example, filter other members in or out based on their credibility rating or current or past location during an event. The Social Eden platform must also enable data mining to verify facts and communicate messages. Some of these visualization tools would be interactive and others would be static—especially the communication tools. Key sites in the dataviz community display countless examples of stunning infographics that combine business intelligence and data visualizations in social media. The wealth of visualizations on Visualizing.org is impressive, especially for social media. For examples Figure 19. Home page on Visualizing.org of these visualizations, see Appendix B: Data visualizations.
56 Microsoft GrapeVine, “Practical uses for Microsoft Vine,” May 14, 2009
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6 Conclusion Social media, mobile devices, and user-generated content are changing every aspect of how people communicate and consume information. We’ve outlined an approach to leverage this spectacular growth by creating a new, robust, and generic platform to support emerging technologies, communication methods, and ways to share information. This platform would differentiate itself from existing solutions in its ability to support the missing trust among members of its communities and in its ability to follow a community’s life cycle by mimicking real-world social life cycles and providing state-of-the-art trust mechanisms and community-sensing sentiment sensors that continuously provide relevant stimulus. Just as cloud computing is the industrialization of traditional IT, our proposed Social Edens system—an event-driven, automatically managed, and optimized social platform and life cycle—represents the industrialization of social media. It would provide fast scalability and vast economies of scale for cybersocial growth. The models to commercialize this space already exist and are robust. They include e- commerce, services, cloud hosting, and hardware integration. End-to-end control of the system’s supply chain would have a positive impact on the social stickiness of this model. Something like our proposed Social Edens system is how social media will inevitably evolve next, so time is of the essence for any software player that wants to develop it. The key technologies and resources are already available to build this kind of compelling social media platform that could bind hundreds of millions of users into event- and interest-based communities. Who will dominate this space?
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7 Appendix A: Research This appendix includes references to and quotations from papers and technologies that would be very useful in developing the Social Eden platform.
“Robust space transformations for distance-based operations” http://infolab.usc.edu/csci599/Fall2002/paper/DR1_robust-space-transformations-for.pdf This paper discusses distance-based clustering, which the Social Eden platform would use. “For many KDD operations, such as nearest neighbor search, distance-based clustering, and outlier detection, there is an underlying KDD data space in which each tuple/object is represented as a point in the space. In the presence of differing scales, variability, correlation, and/or outliers, we may get unintuitive results if an inappropriate space is used. “
Wikipedia: “Cluster analysis” http://en.wikipedia.org/wiki/Cluster_analysis This entry discusses distance-based clustering, which the Social Eden platform would use. “Cluster analysis or clustering is the task of assigning a set of objects into groups (called clusters) so that the objects in the same cluster are more similar (in some sense or another) to each other than to those in other clusters…Popular notions of clusters include groups with low distances among the cluster members, dense areas of the data space, intervals or particular statistical distributions. Clustering can therefore be formulated as a multi-objective optimization problem.” The image to the left is of several distance-based clusters, which could be formed from aggregations of the kinds of observations or Figure 20. Distance-based facts that Social Edens would create. The external rings of each clusters cluster contain outliers that in many cases can or should be ignored.
“Supporting Trust in Virtual Communities” www.sce.carleton.ca/faculty/esfandiari/agents/papers/abdulrahman.pdf This paper makes clear that trust, like truth, is subjective, and it discusses the concept of subjective probability to suggest that there are different levels of trust. The paper also discusses how to evaluate semantic distance. “At any given time, the stability of a community depends on the right balance of trust and distrust. Furthermore, we face information overload, increased uncertainty and risk taking as a prominent feature of modern living. As members of society, we cope with these complexities and uncertainties by relying on trust, which is the basis of all social interactions. Although a small number of trust models have been proposed for the virtual medium, we find that they are largely impractical and artificial. In this paper we provide and discuss a trust model that is grounded in real-world social trust characteristics, and based on a reputation mechanism, or word-of-mouth. Our proposed model allows agents to decide which other agents’ opinions they trust more and allows agents to progressively tune their understanding of another agent’s subjective recommendations…Our aim is to provide a trust model based on the real world social properties of trust, founded on work from the social sciences…
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“Trust is a social phenomenon. As such, any artificial model of trust must be based on how trust works between people in society. For our purposes, however, we find it instructive to use the following definition by Gambetta: …trust (or, symmetrically, distrust) is a particular level of the subjective probability with which an agent will perform a particular action, both before [we] can monitor such action (or independently of his capacity of ever to be able to monitor it) and in a context in which it affects [our] own action. “Mathematical probability has certain properties that make it unsuitable as a trust metric, which will be discussed in Section 2.3. For this reason, we will take Gambetta’s use of the term ‘subjective probability’ above only as an indication of the existence of different levels of trust, which are dependent upon the truster.”
“Trust Formation in New Organizational Relationships” www.misrc.umn.edu/wpaper/WorkingPapers/9601.pdf This paper discusses three types of trust: Interpersonal trust. One party’s willingness to depend on the other party with a feeling of relative security even though negative consequences are possible. System trust. The belief that proper impersonal structures are in place to enable one to anticipate a successful future endeavor. Dispositional trust. The level of trust that someone has if they have a consistent tendency to trust across a broad spectrum of situations and persons.
“A Reputation-based Trust Model with Fuzzy Approach and D -Distance Technique for Peer-to-Peer Networks” http://research.ijcaonline.org/volume37/number12/pxc3876751.pdf This paper proposes a reputation-based trust model for peer-to-peer networks that could be used in the Social Eden. The developers of the Social Eden platform could adopt this decentralized agent-based approach so that agents (Social Eden members) can share a level of individual trust with other members when the same members appear in different Social Edens. The paper states, “Trust policies and trust evaluation mechanisms are needed for quantifying and comparing the trust worthiness of peers. In this paper we propose a trust evaluating model based on reputation and statistical technique.”
“Sports doping: Racing just to keep up” www.nature.com/news/2011/150711/full/475283a.html
“Aiding the Detection of Fake Accounts in Large Scale Social Online Services” www.cs.duke.edu/~msirivia/publications/sybilrank-tech-report.pdf Sadly, fake Social Eden accounts could be used for malicious activities and spread inappropriate or illegal content. This paper addresses this problem by proposing a clever system called SybilRank to improve trust among Social Eden members and, by extension, among marketers who may fear diluting the effectiveness of their advertising in untrustworthy Social Edens. “Users increasingly rely on the trustworthiness of the information exposed on Online Social Networks (OSNs). In addition, OSN providers base their business models on the marketability of this information. However, OSNs suffer from abuse in the form of the creation of fake accounts, which do not correspond to real humans. Fakes can introduce spam, manipulate online rating, or exploit knowledge extracted from the network. OSN operators currently expend significant resources to detect, manually verify, and shut
Page 33 Social Edens Building, mining, and monetizing dynamic online communities down fake accounts. Tuenti, the largest OSN in Spain, dedicates 14 full-time employees in that task alone, incurring a significant monetary cost. Such a task has yet to be successfully automated because of the difficulty in reliably capturing the diverse behavior of fake and real OSN profiles. We introduce a new tool in the hands of OSN operators, which we call SybilRank. It relies on social graph properties to rank users according to their perceived likelihood of being fake (Sybils). SybilRank is computationally efficient and can scale to graphs with hundreds of millions of nodes, as demonstrated by our Hadoop prototype. We deployed SybilRank in Tuenti’s operation center. We found that ∼90% of the 200K accounts that SybilRank designated as most likely to be fake, actually warranted suspension. On the other hand, with Tuenti’s current user-report-based approach only ∼5% of the inspected accounts are indeed fake…Some fakes are created to increase the visibility of niche content, forum posts, and fan pages by manipulating votes or view counts. Fake accounts are also used in political campaigns.”
“Applications of Social Network Analysis to Community Dynamics” www.serc.iisc.ernet.in/graduation-theses/Naimisha_thesis.pdf
“Conceptual Ontology Enrichment for Web Information Retrieval” http://myemea/sites/helgeso/Shared%20Documents/Misc/2011-SteinThomassen_PhD_thesis.pdf (Stein L. Tomassen, Doctoral thesis at Norwegian University of Science and Technology, 2011) “The aim of this work is to find an effective approach for applying ontologies to existing search systems. The basic idea is that these ontologies can be used to tackle the problem of ambiguous words and hence improve the retrieval effectiveness. Our approach to semantic search builds on feature vectors (FV).”
“A Framework for Temporal Geographic Information” http://utpjournals.metapress.com/content/k877727322385q6v/fulltext.pdf This paper describes how cartographers can use similarities between time and place to represent both visually—an important function of the Social Eden platform. “This paper defines the critical components of cartographic time and compares temporal and spatial topologies. Because time is topologically similar to space, spatial data structuring principles can be adapted to temporal data. We present three conceptualizations of temporal geographic information and select one as the most promising basis for a temporal geographic information system. This conceptualization creates a spatial composite of all geometric information (at all times), where each object has an attribute history distinct from that of its neighbors.”
“Multi-dimensional evidence-based trust management with multi-trusted paths” http://astro.temple.edu/~tua83741/jiewu/publications/2010/6.pdf “Trust management is an extensively investigated topic. A lot of trust models and systems have been proposed in the literature. However, a universally agreed trust model is rarely seen due to the fact that trust is essentially subjective and different people may have different views on it. We focus on the personalization of trust in order to catch this subjective nature of trust. We propose a multi-dimensional evidence-based trust management system with multi-trusted paths (MeTrust for short) to conduct trust computation on any arbitrarily complex trusted graph. The trust computation in MeTrust is conducted at three tiers, namely, the node tier, the path tier, and the graph tier. At the node tier, we consider multi- dimensional trust. Users can define a primary dimension and alternative dimensions on their own and users can make their own privileged strategies and setup weights for different dimensions for trust computation. At the path tier, we propose to use the Frank t-norm for users to control the decay rate for trust combination, which can be tuned in between the minimum trust combination (there is no decay in
Page 34 Social Edens Building, mining, and monetizing dynamic online communities terms of the path length) and the product trust combination (the decay is too fast when the path length is relatively large). At the graph tier, we propose GraphReduce, GraphAdjust, and WeightedAverage algorithms to simplify any arbitrarily complex trusted graph. We employ trust truncation and trust equivalence to guarantee that every link in the graph will be used exactly once for trust computation. We evaluated trust truncation ratio and trust success ratio through extensive experiments, which can serve as a guide for users to select from a wide spectrum of trust parameters for trust computation.”
“Revision of LSCOM Event/Activity Annotations” www.ee.columbia.edu/~lyndon/pubs/adventtr2006-event.pdf www-nlpir.nist.gov/projects/tv2005/LSCOMlite_NKKCSOH.pdf A funding agency in the U.S. National Security Agency called the Disruptive Technology Office (DTO) and Columbia University have jointly developed a large-scale concept ontology for multimedia (LSCOM), which lets users categorize multimedia and thus news clips into about one of 1000 “concepts [related to] events, objects, locations, people and programs.” The university used volunteers to develop basic ontological categories such as airplane, airplane taking off, airplane landing, and airplane flying. The ontology, which is downloadable, is an example of how to tag event-related media so that it’s machine- readable on the Semantic Web. The following figure shows a snippet of the LSCOM ontology.
Figure 21. LSCOM ontology example
“Video Event Classification using String Kernels” http://www.micc.unifi.it/publications/2010/BBDS10/MTAP10.pdf This paper discusses another attempt to create an ontology with which to classify video bits. “Event recognition is a crucial task to provide high-level semantic description of the video content. The bag-of- words (BoW) approach has proven to be successful for the categorization of objects and scenes in images, but it is unable to model temporal information between consecutive frames. In this paper we present a method to introduce temporal information for video event recognition within the BoW approach. Events are modeled as a sequence composed of histograms of visual features, computed from each frame using the traditional BoW. The sequences are treated as strings (phrases) where each histogram is considered as a character.”
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“WonderWeb Deliverable D18” http://wonderweb.semanticweb.org/deliverables/documents/D18.pdf This paper, part of the WonderWeb project to develop a library of foundational ontologies to empower the Semantic Web, discusses a “descriptive ontology for linguistic and cognitive engineering” (DOLCE). As the paper states, “DOLCE was not intended as a candidate for a ‘universal’ standard ontology, but rather as a reference module, to be adopted as a starting point for comparing and elucidating the relationships with other future modules of the library...and also for clarifying the hidden assumptions underlying existing ontologies or linguistic resources such as WordNet.”
“The Social Nature of Information and the Role of Trust” www.academia.edu/attachments/19883103/download_file This paper discusses several crucial aspects of information in IT, specifically in relation to information agents. “If information per se is a social construct, then its technology should be socially designed and integrated, and that machines must be involved in real social relationships because they have to mediate them among humans….In particular, there are two categories of metabeliefs…Competence and trustworthiness of the source.”
“Searching Social Media” www.hindawi.com/journals/ivp/2009/856037/ Abstract: We present a novel profile-based focused crawling system for dealing with the increasingly popular social media-sharing websites. In this system, we treat the user profiles as ranking criteria for guiding the crawling process. Furthermore, we divide a user’s profile into two parts, an internal part, which comes from the user’s own contribution, and an external part, which comes from the user’s social contacts. To expand the crawling topic, a cotagging topic-discovery scheme was adopted for social media-sharing websites. Crawling, a path string-based page classification method, is first developed for identifying list pages, detail pages, and profile pages. The identification of the correct type of page is essential for our crawling, because we want to distinguish between list, profile, and detail pages to extract the correct information from each type of page, and subsequently estimate a reasonable ranking for each link that is encountered while crawling. Our experiments prove the robustness of our profile-based focused crawler, as well as a significant improvement in harvest ratio, compared to breadth-first and online page importance computation (OPIC) crawlers, when crawling the Flickr website for two different topics. Introduction: Social media-sharing websites such as Flickr and YouTube are becoming increasingly popular. These websites not only allow users to upload, maintain, and annotate media objects such as images and videos, but also allow them to socialize with other people through contacts, groups, subscriptions, and so forth. Two types of information are generated in this process. The first type of information is the rich text, tags, and multimedia data uploaded and shared on such websites. The second type of information is the users’ profile information, which can tell us what kind of interests they have. Research on how to use the first type of information has gained momentum recently. However, little attention has been paid to effectively exploit the second type of information, the user profiles, to enhance focused search on social media websites. In recent years, another kind of information—the members’ profiles—started playing a prominent role in social networking and resource-sharing sites. Unfortunately, this valuable information still eludes all current focused crawling efforts.
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“Model-Based Clustering for Social Networks” www.stat.washington.edu/raftery/Research/PDF/Handcock2007.pdf Mark S. Handcock, Adrian E. Raftery and Jeremy M. Tantrum, University of Washington, Working Paper no. 46, Center for Statistics and the Social Sciences, University of Washington, April 27, 2005 “A feature of most social networks is transitivity of relations whereby two actors that have ties to a third actor are more likely to be tied than actors that do not. Transitivity has been extensively studied both empirically and theoretically (White, Boorman, and Breiger 1976). Transitivity can lead to some clustering of relationships within the network… The likelihood of a link usually depends on attributes of the actors. For example, for most social relations the likelihood of a relationship is a function of the age, gender, geography and race of the individuals. Homophily by attributes usually implies increased probability of a tie (McPherson, Smith-Lovin, and Cook, 2001), although the effect may be reversed (e.g., gender and sexual relationships).”
“Social Media’s Productivity Payoff” http://blogs.hbr.org/cs/2012/08/social_medias_productivity_pay.html This Harvard Business Review article asserts that social technologies are “not giant time sinks that keep your employees from getting their work done” but in fact “may become the most powerful tools yet developed to raise the productivity of high-skill knowledge workers… Companies are beginning to discover that social technology platforms provide a far more efficient way of communicating and collaborating….The total potential value at stake in these sectors is $900 billion to $1.3 trillion annually…Two-thirds would arise from using social technologies to improve the collaboration and communications of knowledge workers within these functions and across the enterprise.”
“Social Media and Political Engagement” www.pewinternet.org/Reports/2012/Political-engagement.aspx This report by the Pew Internet and American Life project states that “66% of social media users have employed the platforms to post their thoughts about civic and political issues, react to others’ postings, press friends to act on issues and vote, follow candidates, ‘like’ and link to others’ content, and belong to groups formed on social networking sites… Most [Facebook users] — 81 per cent — live outside of the U.S. and Canada. Many of them log in on mobile devices rather than personal computers, and the company now has 600 million mobile users.”
“What Is Identity (As We Now Use the Word)?” http://www.stanford.edu/~jfearon/papers/iden1v2.pdf This paper from the Stanford Department of Political Science analyzes the multiple meanings of the word “identity” in the social sciences and humanities.
“Self and Social Identity” http://www1.psych.purdue.edu/~willia55/392F/EllemersSpearsDoosje.pdf This paper’s authors argue that “group commitment, on the one hand, and features of the social context, on the other hand, are crucial determinants of central identity concerns.” The authors “develop a taxonomy of situations to reflect the different concerns and motives that come into play as a result of threats to personal and group identity and degree of commitment to the group.”
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“A Report on U.S. and Canadian Consumer Attitudes About Trust, Relevance and the Data Value Exchange” http://loyalty.com/sites/default/files/07-0240%20Privacy%20whitepaper_17_r1.pdf This report, based on extensive survey with consumers, discusses why consumers are leery of how companies maintain their personal data. “Based on our findings, consumer trust appears to be fading as quickly as a morning star. And if organizations do not act decisively to demonstrate that they have the consumer’s best interest at heart, they risk a continued erosion of confidence. More than three-quarters of survey respondents―78%―do not feel they receive any benefit at all from sharing information, up from 74% in 2011…In fact, only 42% of consumers trust companies with their personal information, according to the study.”
“Dimitry Maex on data privacy” http://sellorelse.ogilvy.com/2012/09/03/dimitri-maex-on-data-privacy/ Maex, managing director of OgilvyOne in New York, says, “Data privacy is a huge issue and a very emotional issue at the moment because a lot of people—rightly so—are very concerned about their privacy and about all the data companies are collecting. What I think you’re going to see in the next couple of years is that the conversation is going to change and its’ going to turn from the negative to the positive. We’re recently done some research that suggests that people are a lot more open to sharing data as long as they’re getting value from that. So I think companies are going to need to figure out how to extract value for their customers using that data.”
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8 Appendix B: Data visualizations The following data visualization examples come from www.visualizing.org.
8.1 Visualization of defections in Syria This visualization from the Al Jazeera website shows military officials, members of parliament, and diplomats who have defected from the regime of Bashar al-Assad of Syria.57
Figure 22. Visualizing Syria’s defections
8.2 Breast cancer conversations This visualization illustrates conversations by Twitter users. Circles that represent users show how often they tweet or retweet about breast cancer.58 As the site’s creators say, “Want to know what’s going on with breast cancer? Here, we take a close look at the ongoing conversation happening among Twitter’s millions of users. Take a look and then join the conversation.”
57 Aljazeera, “Tracking Syria’s Defections” August 9, 2012 58 GE Data Visualization, visualizing.org, “The Breast Cancer Conversation,” Visualizing.org, September 15, 2011
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Figure 23. Breast cancer conversation
8.3 Recent Spanish uprisings This visualization shows the distribution of tweets during the continuing Spanish uprisings. An account is included if it has eight or more connections (a friend or follower) to certain seed accounts.59
Figure 24. Twitter accounts leading the recent Spanish uprisings
59 Manuela Lucas, “Spanish Revolution at Twitter,” February 12, 2012
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8.4 Newshound Creative agency JESS3, which specializes in data visualizations, built a Facebook application (shown in the following two figures) that makes The Wall Street Journal’s weekly Newshound current events quiz more interactive and shareable.60
Figure 25. Newshound Facebook application
60 JESS3, “The Wall Street Journal Newshound Facebook Application”
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Figure 26. Detail from Newshound Facebook application
8.5 Microsoft acquisitions and investments This infographic on Ripetungi.com shows Microsoft acquisitions and investments over time as a tube map, with each colored line representing a different industry for each acquisition or investment.61 Every dot in Figure 28 below could refer to a Social Eden based on an acquisition.
Figure 27. Microsoft acquisitions and investments map
61 Ripetungi, “Microsoft acquisitions and investments”
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Figure 28. Detail from Microsoft acquisitions and investments map
8.6 Psychoanalyzing the presidential debates in real time Part data visualization, part experimental typography, ReConstitution 2012 (www.recon12.com) is a Web app that parses the language of the presidential debates in real time and creates an animated “psychoanalysis” of the transcript. CNN says, “As a live transcription of the debate unfurls on the ReConstitution site, words and stats are instantly highlighted and annotated with bright colors. Clicking on a highlighted word tells you why it was called out: say, for ambiguous, gloomy or bullish language…The psychoanalyzing is powered on the back end by a program called Linguistic Inquiry and Word Count, a project from the University of Texas at Austin that is also used by the U.S. government and law enforcement. It looks at factors such as word count, types of pronouns and its own dictionary of 4,500 words and word stems divided into various categories…based on scholarly research.”62
62 Heather Kelly, “App promises to psychoanalyze debates in real time,” CNN, October 16, 2012
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Figure 29. ReConstitution 2012 animation from the second Obama-Romney debate
8.7 Wavii Wavii, a Seattle company, offers a new, personalized streaming service that’s based on machine learning of text across the Internet. Unlike Facebooks’ news feeds, which are based on status updates and content shared by friends, Wavii’s feeds collect and display material from across the entire Internet, including news articles, blog posts, and tweets. Wavii thus feeds news about what’s going on in the world instead of thoughts and links from friends and family. As the BBC describes it, “The startup’s ‘learning’ algorithms kick in to crawl the real-time web, and turn plain facts and unstructured content into something endowed with context and order… The technology, which processes up to 1,000 articles a minute, can detect rumours and story duplicates, ultimately streaming the most important and relevant nuggets of information into new feeds.”63 In the beta version of the service, users choose up to 12 topics or people to follow in their personalized news feed, though they can later add other interests to follow. Wavii hosts some of its data visualizations as “experiments” on their own sites. Wavii’s technologists are veterans of Microsoft, Amazon, Yahoo, and Fox Interactive Media. On April 23, 2013, Google announced that it had acquired Wavii and would integrate its features into Google’s products.
63 Laura Locke, “Wavii poses a challenge to Facebook's news feed,” BBC, April 11, 2012
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Figure 30. Wavii news stream “experiment”
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Jess3 creative agency (http://jess3.com/) Ripetungi. “Microsoft acquisitions and investments” (http://ripetungi.com/microsoft-acquisitions-and- investments) Heather Kelly. “App promises to psychoanalyze debates in real time.” CNN, October 16, 2012 (www.cnn.com/2012/10/16/tech/web/reconstitution-debate-tool/index.html) Laura Locke. “Wavii poses a challenge to Facebook's news feed.” BBC, April 11, 2012 (www.bbc.com/news/technology-17684406)
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