The Emoji Factor: Humanizing the Emerging Law of Digital Speech
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The Origins of the Underline As Visual Representation of the Hyperlink on the Web: a Case Study in Skeuomorphism
The Origins of the Underline as Visual Representation of the Hyperlink on the Web: A Case Study in Skeuomorphism The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Romano, John J. 2016. The Origins of the Underline as Visual Representation of the Hyperlink on the Web: A Case Study in Skeuomorphism. Master's thesis, Harvard Extension School. Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:33797379 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA The Origins of the Underline as Visual Representation of the Hyperlink on the Web: A Case Study in Skeuomorphism John J Romano A Thesis in the Field of Visual Arts for the Degree of Master of Liberal Arts in Extension Studies Harvard University November 2016 Abstract This thesis investigates the process by which the underline came to be used as the default signifier of hyperlinks on the World Wide Web. Created in 1990 by Tim Berners- Lee, the web quickly became the most used hypertext system in the world, and most browsers default to indicating hyperlinks with an underline. To answer the question of why the underline was chosen over competing demarcation techniques, the thesis applies the methods of history of technology and sociology of technology. Before the invention of the web, the underline–also known as the vinculum–was used in many contexts in writing systems; collecting entities together to form a whole and ascribing additional meaning to the content. -
Seeing Emoji Rendering Differences Across Platforms
What I See is What You Don’t Get: The Effects of (Not) Seeing Emoji Rendering Differences across Platforms HANNAH MILLER HILLBERG, GroupLens Research, University of Minnesota, USA ZACHARY LEVONIAN, GroupLens Research, University of Minnesota, USA DANIEL KLUVER, GroupLens Research, University of Minnesota, USA LOREN TERVEEN, GroupLens Research, University of Minnesota, USA BRENT HECHT, Northwestern University, USA Emoji are popular in digital communication, but they are rendered differently on different viewing platforms (e.g., iOS, Android). It is unknown how many people are aware that emoji have multiple renderings, or whether they would change their emoji-bearing messages if they could see how these messages render on recipients’ devices. We developed software to expose the multi-rendering nature of emoji and explored whether this increased visibility would affect how people communicate with emoji. Through a survey of 710 Twitter users who recently posted an emoji-bearing tweet, we found that at least 25% of respondents were unaware that the emoji they posted could appear differently to their followers. Additionally, after being shown how one of their tweets rendered across platforms, 20% of respondents reported that they would have edited or not sent the tweet. These statistics reflect millions of potentially regretful tweets shared per day because people cannot see emoji rendering differences across platforms. Our results motivate the development of tools that increase the visibility of emoji rendering differences across platforms, and we 1 contribute our cross-platform emoji rendering software to facilitate this effort. 124 CCS Concepts: • Human-centered computing → Empirical studies in collaborative and social computing KEYWORDS Emoji; computer-mediated communication; cross-platform; rendering; invisibility of system status ACM Reference format: Hannah Miller Hillberg, Zachary Levonian, Daniel Kluver, Loren Terveen and Brent Hecht. -
Speaking the Same Language: Data Standards and Disruptive Technologies in the Administration of Justice
Speaking the Same Language: Data Standards and Disruptive Technologies in the Administration of Justice David Colarusso* & Erika J. Rickard** I. INTRODUCTION While the legal profession is coming to grips with technological disruption, practitioners serving the needs of those with low and moderate-incomes find themselves struggling to keep up.1 Insufficient resources clearly impede large- scale technological improvements. Yet, the rise of civic coding and the growing legal technology sector suggest an untapped pool of civic and private resources ready to help address this shortfall.2 We argue that state trial courts are best positioned to leverage these resources for the benefit of low and moderate- income individuals by addressing a key structural impediment to innovation: the lack of clearly-defined judicial data standards. In private practice and legal education, innovative technologies have fueled competition from companies that provide document automation to the general public and leverage machine intelligence to remove the work of repetitive tasks, including matters involving rudimentary questions of judgment.3 While * Data Scientist, Massachusetts Committee for Public Counsel Services (CPCS); J.D., Boston University School of Law (2011); M.Ed., Harvard Graduate School of Education (2002). The opinions expressed here are the author’s own and do not reflect those of CPCS or the Commonwealth of Massachusetts. ** Associate Director of Field Research, Access to Justice Lab at Harvard Law School, and Commissioner, Massachusetts Access to Justice Commission; J.D., Harvard Law School (2010). Portions of this Article derive from presentations made by the authors at the 2016 Suffolk University Law Review’s Legal Technology Symposium entitled, “A New Era of Lawyering: Integrating Law Practice with Innovative Technology.” Additional portions were adapted from a CPCS blog post accompanying a public comment in reply to the Massachusetts Trial Court’s 2016 proposed rule change regarding access to court records. -
Super Duper Semaphore Or, As We Like to Call It
Super Duper Semaphore Or, as we like to call it ... Flag Texting! Hello Lieutenants ... You can have a whole lot of fun with just a couple of hand flags. Even if you don’t have actual flags, you can make your own using items found around your home, like tea towels, or even two smelly old socks tied to some sticks! As long as you’re having fun ... be inventive. What’s it all about? Well, believe it or not, a great way for ships near (in range of) each other or ships wanting to communicate to the land is to use ‘Flag Semaphore’. It’s a bit like sending a text message ... but with your arms. It has been used for hundreds of years on both land and sea (from the sea, red and yellow flags are used). The word semaphore is Greek for ‘Sign-bearer’ Here’s how it works… Each letter of the alphabet has its own arm position (plus a few extras that we will cover in later ranks). Once you can remember these, you can send loads of hidden messages to your friends and family. Check these out ... ABCDEFG HIJKLM NOPQR STUVWX YZ How cool is that? To send a message the ‘sender’ gets the attention of the ‘receiver’ by waving their arms (and flags) by their side in an up and down motion (imagine flapping your arms like a bird). Don’t worry if you make mistakes or the receiver translates your signals into silly words - we’ve had lots of fun practicing this, and it will take time to become a Super Signaller! Are you ready to send your message? One letter at a time? Remember to pause between each letter and a bit longer between words to accurately get your message through. -
Microej Documentation
MicroEJ Documentation MicroEJ Corp. Revision ff3ccfde Nov 27, 2020 Copyright 2008-2020, MicroEJ Corp. Content in this space is free for read and redistribute. Except if otherwise stated, modification is subject to MicroEJ Corp prior approval. MicroEJ is a trademark of MicroEJ Corp. All other trademarks and copyrights are the property of their respective owners. CONTENTS 1 MicroEJ Glossary 2 2 Overview 4 2.1 MicroEJ Editions.............................................4 2.1.1 Introduction..........................................4 2.1.2 Determine the MicroEJ Studio/SDK Version..........................5 2.2 Licenses.................................................7 2.2.1 Overview............................................7 2.2.2 License Manager........................................7 2.2.3 Evaluation Licenses......................................7 2.2.4 Production Licenses......................................9 2.3 MicroEJ Runtime............................................. 13 2.3.1 Language............................................ 13 2.3.2 Scheduler............................................ 13 2.3.3 Garbage Collector....................................... 14 2.3.4 Foundation Libraries...................................... 14 2.4 MicroEJ Libraries............................................ 14 2.5 MicroEJ Central Repository....................................... 15 2.6 Embedded Specification Requests................................... 15 2.7 MicroEJ Firmware............................................ 15 2.7.1 Bootable Binary with -
Emoticon Style: Interpreting Differences in Emoticons Across Cultures
Emoticon Style: Interpreting Differences in Emoticons Across Cultures Jaram Park Vladimir Barash Clay Fink Meeyoung Cha Graduate School of Morningside Analytics Johns Hopkins University Graduate School of Culture Technology, KAIST [email protected] Applied Physics Laboratory Culture Technology, KAIST [email protected] clayton.fi[email protected] [email protected] Abstract emotion not captured by language elements alone (Lo 2008; Gajadhar and Green 2005). With the advent of mobile com- Emoticons are a key aspect of text-based communi- cation, and are the equivalent of nonverbal cues to munications, the use of emoticons has become an everyday the medium of online chat, forums, and social media practice for people throughout the world. Interestingly, the like Twitter. As emoticons become more widespread emoticons used by people vary by geography and culture. in computer mediated communication, a vocabulary Easterners, for example employ a vertical style like ^_^, of different symbols with subtle emotional distinctions while westerners employ a horizontal style like :-). This dif- emerges especially across different cultures. In this pa- ference may be due to cultural reasons since easterners are per, we investigate the semantic, cultural, and social as- known to interpret facial expressions from the eyes, while pects of emoticon usage on Twitter and show that emoti- westerners favor the mouth (Yuki, Maddux, and Masuda cons are not limited to conveying a specific emotion 2007; Mai et al. 2011; Jack et al. 2012). or used as jokes, but rather are socio-cultural norms, In this paper, we study emoticon usage on Twitter based whose meaning can vary depending on the identity of the speaker. -
New Emoji Requests from Twitter Users: When, Where, Why, and What We Can Do About Them
1 New Emoji Requests from Twitter Users: When, Where, Why, and What We Can Do About Them YUNHE FENG, University of Tennessee, Knoxville, USA ZHENG LU, University of Tennessee, Knoxville, USA WENJUN ZHOU, University of Tennessee, Knoxville, USA ZHIBO WANG, Wuhan University, China QING CAO∗, University of Tennessee, Knoxville, USA As emojis become prevalent in personal communications, people are always looking for new, interesting emojis to express emotions, show attitudes, or simply visualize texts. In this study, we collected more than thirty million tweets mentioning the word “emoji” in a one-year period to study emoji requests on Twitter. First, we filtered out bot-generated tweets and extracted emoji requests from the raw tweets using a comprehensive list of linguistic patterns. To our surprise, some extant emojis, such as fire and hijab , were still frequently requested by many users. A large number of non-existing emojis were also requested, which were classified into one of eight emoji categories by Unicode Standard. We then examined patterns of new emoji requests by exploring their time, location, and context. Eagerness and frustration of not having these emojis were evidenced by our sentiment analysis, and we summarize users’ advocacy channels. Focusing on typical patterns of co-mentioned emojis, we also identified expressions of equity, diversity, and fairness issues due to unreleased but expected emojis, and summarized the significance of new emojis on society. Finally, time- continuity sensitive strategies at multiple time granularity levels were proposed to rank petitioned emojis by the eagerness, and a real-time monitoring system to track new emoji requests is implemented. -
Researchers Take a Closer Look at the Meaning of Emojis. Like 30
City or Zip Marlynn Wei M.D., J.D. Home Find a Therapist Topics Get Help Magazine Tests Experts Urban Survival Researchers take a closer look at the meaning of emojis. Like 30 Posted Oct 26, 2017 SHARE TWEET EMAIL MORE TO GO WITH AFP STORY BY TUPAC POINTU A picture shows emoji characters also known a… AFP | MIGUEL MEDINA A new database introduced in a recent research paper (https://www.ncbi.nlm.nih.gov/pubmed/28736776)connects online dictionaries of emojis with a semantic network to create the first machine-readable emoji inventory EmojiNet (http://emojinet.knoesis.org). (http://emojinet.knoesis.org) In April 2015, Instagram reported that 40 percent of all messages contained an emoji. New emojis are constantly being added. With the rapid expansion and surge of emoji use, how do we know what emojis mean when we send them? And how do we ensure that the person at the other end knows what we mean? It turns out that the meaning of emojis varies a whole lot based on context. Emojis, derived from Japanese “e” for picture and “moji” for character, were first introduced in the late 1990s but did not become Unicode standard until 2009. Emojis are pictures depicting faces, food, sports (https://www.psychologytoday.com/basics/sport-and- competition), animals, and more, such as unicorns, sunrises, or pizza. Apple introduced an emoji keyboard to iOS in 2011 and Android put them on mobile platforms in 2013. Emojis are different from emoticons, which can be constructed from your basic keyboard, like (-:. The digital use of emoticons has been traced back to as early as 1982, though there are earlier reported cases in Morse code telegraphs. -
A Sociolinguistic Analysis of Emoticon Usage in Japanese Blogs: Variation by Age, Gender, and Topic1
Selected Papers of Internet Research 16: The 16th Annual Meeting of the Association of Internet Researchers Phoenix, AZ, USA / 21-24 October 2015 A SOCIOLINGUISTIC ANALYSIS OF EMOTICON USAGE IN JAPANESE BLOGS: VARIATION BY AGE, GENDER, AND TOPIC1 Yukiko Nishimura Toyo Gakuen University, Japan Introduction This study explores how older men and women express themselves through blogging (Curtain 2004) in Japan, where the elderly population (aged 65 years and up) will comprise an estimated 40 percent of the country’s total population by 2050 (Statistics Bureau 2014), the greatest proportion of any nation in the world. Figure 1: Proportion of elderly by country (aged 65 and above) Source: Statistics Bureau, MIC; Ministry of Health, Labour and Welfare; United Nations. Internet usage among seniors in Japan has also been increasing in recent years, particularly since 2009 (Ministry of Internal Affairs and Communication 2014). One survey on PC penetration rate among elderly household reports that 78% of people surveyed (N=800 by random telephone number dialing) in their 60’s, 54.5 % in their 70’s, and 30.5 % in their 80’s possess PCs (GF Senior Marketing 2012). 1 I would like to express my gratitude to Patricia M. Clancy for her suggestions on this study. Funding for this research from the Japan Society for the Promotion of Science, Kakenhi Category (c) 24520479, for the period of 2012 to 2015 is gratefully acknowledged. Suggested Citation (APA): Nishimura, Y. (2015, October 21-24). A Sociolinguistic Analysis Of Emoticon Usage In Japanese Blogs: Variation By Age, Gender, And Topic. Paper presented at Internet Research 16: The 16th Annual Meeting of the Association of Internet Researchers. -
Conveying Emotions Through Branded Emojis Case: Dice Hunter, Greener Grass Company
Conveying Emotions Through Branded Emojis Case: Dice Hunter, Greener Grass Company Piritta Vaarala BACHELOR’S THESIS December 2020 Media and Arts Interactive Media ABSTRACT Tampereen ammattikorkeakoulu Tampere University of Applied Sciences Degree Programme in Media and Arts Interactive Media VAARALA, PIRITTA: Conveying Emotions Through Branded Emojis Case: Dice Hunter, Greener Grass Company Bachelor's thesis 52 pages, appendices 4 pages December 2020 The purpose of this thesis was to study theory behind the expression of emotions in online communication, its relation to the use of emojis and the design principles of icon creation. The objective was to utilise the findings from these theories and from additional analyses in order to create a custom emoji set for the case game Dice Hunter, to be used on their Discord server. The study was carried out as a project for Dice Hunter’s developer Greener Grass Company. This study consisted of a literature review on the theory subjects, benchmarking conducted on three games that had their own branded Discord emojis, and a sentiment analysis conducted on the emoji usage history and preferences in the Dice Hunter Discord server. A questionnaire-based survey was carried out as a part of the sentiment analysis. The key findings suggested that without the aid of a physical body, emojis were the closest non-verbal cue for expressing emotions in online communication. In order to convey these emotions accurately, emojis needed to be easy to read at a glance but also descriptive enough so that they could be easily distinguished from each other. When asked about their preferences, the majority of the Dice Hunter community members stated that they preferred diversity in expressions over diversity in characters when it came to custom emoji sets. -
A Study of New Emoji Requests Based on Thirty Million Tweets
The World Wants Mangoes and Kangaroos: A Study of New Emoji Requests Based on Thirty Million Tweets Yunhe Feng1, Wenjun Zhou1, Zheng Lu1, Zhibo Wang2, Qing Cao1 1University of Tennessee, Knoxville; 2Wuhan University {yfeng14,wzhou4,zlu12,cao}@utk.edu,[email protected] ABSTRACT was using emojis. With the popularity of social networks, nowadays, As emojis become prevalent in personal communications, people emojis are used extensively on various social networking platforms, are always looking for new, interesting emojis to express emotions, such as Twitter, Facebook, WhatsApp, and Instagram. In particular, show attitudes, or simply visualize texts. In this study, we collected nearly half of comments and captions on Instagram have emojis [9]. more than thirty million tweets mentioning the word “emoji” in As the usage of emojis (and social media in general) evolves, a one-year period to study emoji requests on Twitter. First, we new emojis are being continuously requested. The Unicode Con- 1 filtered out bot-generated tweets and extracted emoji requests from sortium updates the official list of Unicode emojis by judging and the raw tweets using a comprehensive list of linguistic patterns. accepting proposals for new emojis annually. For each candidate Then, we examined patterns of new emoji requests by exploring emoji, its evidence of frequency from Google Search, Bing Search, their time, locations, and context. Finally, we summarized users’ Youtube Search and Google Trends must be submitted, and ev- advocacy behaviors and identified expressions of equity, diversity, idence from NGram Viewer and Wikipedia Search are optional. and fairness issues due to unreleased but expected emojis, and Besides substantial efforts to collect such evidence, this method has concluded the significance of new emojis on society. -
Windows Rootkit Analysis Report
Windows Rootkit Analysis Report HBGary Contract No: NBCHC08004 SBIR Data Rights November 2008 Page 1 Table of Contents Introduction ................................................................................................................................... 4 Clean Monitoring Tool Logs......................................................................................................... 5 Clean System PSList ................................................................................................................. 5 Clean System Process Explorer ................................................................................................ 6 Vanquish......................................................................................................................................... 7 PSList Vanquish ........................................................................................................................ 7 Vanquish Process Monitor (Process Start – Exit) .................................................................. 8 Process Explorer Thread Stack Vanquish .............................................................................. 8 Process Monitor Events Vanquish ........................................................................................... 9 Vanquish Log File (Created by rootkit, placed in root directory “C:”) ............................. 21 Process Explorer Memory Strings Vanquish ........................................................................ 23 NTIllusion....................................................................................................................................