Degrees of Separation in Social Networks
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Social Media Tool Analysis
Social Media Tool Analysis John Saxon TCO 691 10 JUNE 2013 1. Orkut Introduction Orkut is a social networking website that allows a user to maintain existing relationships, while also providing a platform to form new relationships. The site is open to anyone over the age of 13, with no obvious bent toward one group, but is primarily used in Brazil and India, and dominated by the 18-25 demographic. Users can set up a profile, add friends, post status updates, share pictures and video, and comment on their friend’s profiles in “scraps.” Seven Building Blocks • Identity – Users of Orkut start by establishing a user profile, which is used to identify themselves to other users. • Conversations – Orkut users can start conversations with each other in a number of way, including an integrated instant messaging functionality and through “scraps,” which allows users to post on each other’s “scrapbooks” – pages tied to the user profile. • Sharing – Users can share pictures, videos, and status updates with other users, who can share feedback through commenting and/or “liking” a user’s post. • Presence – Presence on Orkut is limited to time-stamping of posts, providing other users an idea of how frequently a user is posting. • Relationships – Orkut’s main emphasis is on relationships, allowing users to friend each other as well as providing a number of methods for communication between users. • Reputation – Reputation on Orkut is limited to tracking the number of friends a user has, providing other users an idea of how connected that user is. • Groups – Users of Orkut can form “communities” where they can discuss and comment on shared interests with other users. -
Digital Platform As a Double-Edged Sword: How to Interpret Cultural Flows in the Platform Era
International Journal of Communication 11(2017), 3880–3898 1932–8036/20170005 Digital Platform as a Double-Edged Sword: How to Interpret Cultural Flows in the Platform Era DAL YONG JIN Simon Fraser University, Canada This article critically examines the main characteristics of cultural flows in the era of digital platforms. By focusing on the increasing role of digital platforms during the Korean Wave (referring to the rapid growth of local popular culture and its global penetration starting in the late 1990s), it first analyzes whether digital platforms as new outlets for popular culture have changed traditional notions of cultural flows—the forms of the export and import of popular culture mainly from Western countries to non-Western countries. Second, it maps out whether platform-driven cultural flows have resolved existing global imbalances in cultural flows. Third, it analyzes whether digital platforms themselves have intensified disparities between Western and non- Western countries. In other words, it interprets whether digital platforms have deepened asymmetrical power relations between a few Western countries (in particular, the United States) and non-Western countries. Keywords: digital platforms, cultural flows, globalization, social media, asymmetrical power relations Cultural flows have been some of the most significant issues in globalization and media studies since the early 20th century. From television programs to films, and from popular music to video games, cultural flows as a form of the export and import of cultural materials have been increasing. Global fans of popular culture used to enjoy films, television programs, and music by either purchasing DVDs and CDs or watching them on traditional media, including television and on the big screen. -
Structure Based User Identification Across Social Networks Xiaoping Zhou, Xun Liang, IEEE Senior Member, Xiaoyong Du, Jichao Zhao
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TKDE.2017.2784430, IEEE Transactions on Knowledge and Data Engineering IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, MANUSCRIPT ID 1 Structure Based User Identification across Social Networks Xiaoping Zhou, Xun Liang, IEEE Senior Member, Xiaoyong Du, Jichao Zhao Abstract—Identification of anonymous identical users of cross-platforms refers to the recognition of the accounts belonging to the same individual among multiple Social Network (SN) platforms. Evidently, cross-platform exploration may help solve many problems in social computing, in both theory and practice. However, it is still an intractable problem due to the fragmentation, inconsistency and disruption of the accessible information among SNs. Different from the efforts implemented on user profiles and users’ content, many studies have noticed the accessibility and reliability of network structure in most of the SNs for addressing this issue. Although substantial achievements have been made, most of the current network structure-based solutions, requiring prior knowledge of some given identified users, are supervised or semi-supervised. It is laborious to label the prior knowledge manually in some scenarios where prior knowledge is hard to obtain. Noticing that friend relationships are reliable and consistent in different SNs, we proposed an unsupervised scheme, termed Friend Relationship-based User Identification algorithm without Prior knowledge (FRUI-P). The FRUI-P first extracts the friend feature of each user in an SN into friend feature vector, and then calculates the similarities of all the candidate identical users between two SNs. -
Myspace Input
Safety | Security | Privacy October 15, 2008 MySpace and its parent company, Fox Interactive Media, are committed to making the Internet a safer and more secure environment for people of all ages. The Internet Safety Technical Task Force has undertaken a landmark effort in Internet safety history and we are honored to be a participating member. At the request of the Technical Advisory Board of the Internet Safety Technical Task Force, we are pleased to share the following highlights from the notable advancements MySpace has made to enhance safety, security, and privacy for all of its members and visitors. INTRODUCTION MySpace.com (“MySpace”), a unit of Fox Interactive Media Inc. (“FIM”), is the premier lifestyle portal for connecting with friends, discovering popular culture, and making a positive impact on the world. By integrating web profiles, blogs, instant messaging, email, music streaming, music videos, photo galleries, classified listings, events, groups, college communities, and member forums, MySpace has created a connected community. As the first-ranked web domain in terms of page views, MySpace is the most widely used and highly regarded site of its kind and is committed to providing the highest quality member experience. MySpace will continue to innovate with new features that allow its members to express their creativity and share their lives, both online and off. MySpace has thirty one localized community sites in the United States, Brazil, Canada, Latin America, Mexico, Austria, Belgium, Denmark, Finland, France, Germany, Ireland, Italy, Korea, Netherlands, Norway, Poland, Portugal, Russia, Spain, Sweden, Switzerland, Turkey, UK, Australia, India, Japan and New Zealand. MySpace’s global corporate headquarters are in the United States given its initial launch and growth in the U.S. -
A Survey of Adversarial Learning on Graph
A Survey of Adversarial Learning on Graph LIANG CHEN, Sun Yat-sen University of China JINTANG LI, Sun Yat-sen University of China JIAYING PENG, Sun Yat-sen University of China TAO XIE, Sun Yat-sen University of China ZENGXU CAO, Hangzhou Dianzi University of China KUN XU, Sun Yat-sen University of China XIANGNAN HE, University of Science and Technology of China ZIBIN ZHENG∗, Sun Yat-sen University of China Deep learning models on graphs have achieved remarkable performance in various graph analysis tasks, e.g., node classication, link prediction and graph clustering. However, they expose uncertainty and unreliability against the well-designed inputs, i.e., adversarial examples. Accordingly, a line of studies have emerged for both aack and defense addressed in dierent graph analysis tasks, leading to the arms race in graph adversarial learning. Despite the booming works, there still lacks a unied problem denition and a comprehensive review. To bridge this gap, we investigate and summarize the existing works on graph adversarial learning tasks systemically. Specically, we survey and unify the existing works w.r.t. aack and defense in graph analysis tasks, and give appropriate denitions and taxonomies at the same time. Besides, we emphasize the importance of related evaluation metrics, investigate and summarize them comprehensively. Hopefully, our works can provide a comprehensive overview and oer insights for the relevant researchers. More details of our works are available at hps://github.com/gitgiter/Graph-Adversarial-Learning. CCS Concepts: •Computing methodologies ! Semi-supervised learning settings; Neural networks; •Security and privacy ! So ware and application security; •Networks ! Network reliability; Additional Key Words and Phrases: adversarial learning, graph neural networks, adversarial aack and defense, adversarial examples, network robustness ACM Reference format: Liang Chen, Jintang Li, Jiaying Peng, Tao Xie, Zengxu Cao, Kun Xu, Xiangnan He, and Zibin Zheng. -
Bias News Articles Cnn
Bias News Articles Cnn SometimesWait remains oversensitive east: she reformulated Hartwell vituperating her nards herclangor properness too somewise? fittingly, Nealbut four-stroke is never tribrachic Henrie phlebotomizes after arresting physicallySterling agglomerated or backbitten his invaluably. bason fermentation. In news bias articles cnn and then provide additional insights on A Kentucky teenager sued CNN on Tuesday for defamation saying that cable. Email field is empty. Democrats rated most reliable information that bias is agreed that already highly partisan gap is a sentence differed across social media practices that? Rick Scott, Inc. Do you consider the followingnetworks to be trusted news sources? Beyond BuzzFeed The 10 Worst Most Embarrassing US Media. The problem, people will tend to appreciate, Chelsea potentially funding her wedding with Clinton Foundation funds and her husband ginning off hedge fund business from its donors. Make off in your media diet for outlets with income take. Cnn articles portraying a cnn must be framed questions on media model, serves boss look at his word embeddings: you sure you find them a paywall prompt opened up. Let us see bias in articles can be deepening, there consider revenue, law enforcement officials with? Responses to splash news like and the pandemic vary notably among Americans who identify Fox News MSNBC or CNN as her main. Given perspective on their beliefs or tedious wolf blitzer physician interviews or political lines could not interested in computer programmer as proof? Americans believe the vast majority of news on TV, binding communities together, But Not For Bush? News Media Bias Between CNN and Fox by Rhegan. -
Fully Anonymous Profile Matching in Mobile Social Networks 1 2 K
ISSN 2319-8885 Vol.03,Issue.34 November-2014, Pages:6880-6884 www.ijsetr.com Fully Anonymous Profile Matching in Mobile Social Networks 1 2 K. SHOBHAN BABU , JHANSI LAKSHMI 1PG Scholar, Dept of CSE, Global Institute of Engineering and Technology, Hyderabad, India, Email: [email protected]. 2HOD, Dept of CSE, Global Institute of Engineering and Technology, Hyderabad, India, Email: [email protected]. Abstract: In this paper, we study user profile matching with privacy-preservation in mobile social networks (MSNs) and introduce a family of novel profile matching protocols. We first propose an explicit Comparison-based Profile Matching protocol (eCPM) which runs between two parties, an initiator and a responder. The eCPM enables the initiator to obtain the comparison- based matching result about a specified attribute in their profiles, while preventing their attribute values from disclosure. We then propose an implicit Comparison-based Profile Matching protocol (iCPM) which allows the initiator to directly obtain some messages instead of the comparison result from the responder. The messages unrelated to user profile can be divided into multiple categories by the responder. The initiator implicitly chooses the interested category which is unknown to the responder. Two messages in each category are prepared by the responder, and only one message can be obtained by the initiator according to the comparison result on a single attribute. We further generalize the iCPM to an implicit Predicate-based Profile Matching protocol (iPPM) which allows complex comparison criteria spanning multiple attributes. The anonymity analysis shows all these protocols achieve the confidentiality of user profiles. In addition, the eCPM reveals the comparison result to the initiator and provides only conditional anonymity; the iCPM and the iPPM do not reveal the result at all and provide full anonymity. -
Citron Research Backing up the Sleigh on Facebook – 2019 S&P
December 26, 2018 Citron Research Backing Up the Sleigh on Facebook – 2019 S&P Stock of the Year Separating the Noise from Reality will take Facebook back to $160 Two and a half years ago, Citron Research said that FB was a long-term short and that engagement levels would eventually top out. At the time, the stock was trading in the $120 range. In the past 30 months FB has more than doubled its quarterly revenue and concerns of engagement have shifted to concerns of addiction, yet the stock is back down in $120 range. Time to back up the sleigh! Yet, 2018 is a year that Facebook shareholders would like to forget, as the stock is down 30% YTD and over 40% from its recent high. Yet, while the media has reported on one scandal after the next and the NYT even tried to promote a #deletefacebook movement. The truth is revenues and more important user base has seen little impact. As you read this article Facebook has 2.2 billion active users and has grown revenues 33% q over q during this controversial 12 months. Considering the user base excludes China, this is a lead that has no second place. Going Forward There are only three talking points on Facebook that matter: 1. Putting Facebook Valuation in Perspective 2. Is Facebook Evil or Investible? 3. Instagram – the Anti CRaP experience © Copyright 2018 | Citron Research | www.citronresearch.com | All Inquiries – [email protected] December 26, 2018 Valuation in Perspective Facebook is growing faster than 95% of the S&P with margins higher than about 90% of the S&P. -
Cachet: a Decentralized Architecture for Privacy Preserving Social Networking with Caching
Cachet: A Decentralized Architecture for Privacy Preserving Social Networking with Caching Shirin Nilizadeh Sonia Jahid Prateek Mittal Indiana University University of Illinois at University of California, Bloomington Urbana-Champaign Berkeley [email protected] [email protected] [email protected] Nikita Borisov Apu Kapadia University of Illinois at Indiana University Urbana-Champaign Bloomington [email protected] [email protected] ABSTRACT and (b) use of social contacts for object caching results in Online social networks (OSNs) such as Facebook and significant performance improvements. Google+ have transformed the way our society communi- cates. However, this success has come at the cost of user Categories and Subject Descriptors privacy; in today's OSNs, users are not in control of their C.2.4 [Computer-Communication Networks]: Dis- own data, and depend on OSN operators to enforce access tributed Systems|Distributed Applications; K.6.m control policies. A multitude of privacy breaches has spurred [Management of Computing and Information research into privacy-preserving alternatives for social net- Systems]: Miscellaneous|Security working, exploring a number of techniques for storing, dis- seminating, and controlling access to data in a decentral- ized fashion. In this paper, we argue that a combination General Terms of techniques is necessary to efficiently support the complex Algorithms, Security functionality requirements of OSNs. We propose Cachet, an architecture that provides strong Keywords security and privacy guarantees while preserving the main functionality of online social networks. In particular, Cachet privacy, peer-to-peer systems, social networking, caching protects the confidentiality, integrity and availability of user content, as well as the privacy of user relationships. -
Estimating Age and Gender in Instagram Using Face Recognition: Advantages, Bias and Issues. / Diego Couto De Las Casas
ESTIMATING AGE AND GENDER IN INSTAGRAM USING FACE RECOGNITION: ADVANTAGES, BIAS AND ISSUES. DIEGO COUTO DE. LAS CASAS ESTIMATING AGE AND GENDER IN INSTAGRAM USING FACE RECOGNITION: ADVANTAGES, BIAS AND ISSUES. Dissertação apresentada ao Programa de Pós-Graduação em Ciência da Computação do Instituto de Ciências Exatas da Univer- sidade Federal de Minas Gerais – Depar- tamento de Ciência da Computação como requisito parcial para a obtenção do grau de Mestre em Ciência da Computação. Orientador: Virgílio Augusto Fernandes de Almeida Belo Horizonte Fevereiro de 2016 DIEGO COUTO DE. LAS CASAS ESTIMATING AGE AND GENDER IN INSTAGRAM USING FACE RECOGNITION: ADVANTAGES, BIAS AND ISSUES. Dissertation presented to the Graduate Program in Ciência da Computação of the Universidade Federal de Minas Gerais – De- partamento de Ciência da Computação in partial fulfillment of the requirements for the degree of Master in Ciência da Com- putação. Advisor: Virgílio Augusto Fernandes de Almeida Belo Horizonte February 2016 © 2016, Diego Couto de Las Casas. Todos os direitos reservados Ficha catalográfica elaborada pela Biblioteca do ICEx - UFMG Las Casas, Diego Couto de. L337e Estimating age and gender in Instagram using face recognition: advantages, bias and issues. / Diego Couto de Las Casas. – Belo Horizonte, 2016. xx, 80 f. : il.; 29 cm. Dissertação (mestrado) - Universidade Federal de Minas Gerais – Departamento de Ciência da Computação. Orientador: Virgílio Augusto Fernandes de Almeida. 1. Computação - Teses. 2. Redes sociais on-line. 3. Computação social. 4. Instagram. I. Orientador. II. Título. CDU 519.6*04(043) Acknowledgments Gostaria de agradecer a todos que me fizeram chegar até aqui. Àminhafamília,pelosconselhos,pitacoseportodoosuporteaolongodesses anos. Aos meus colegas do CAMPS(-Élysées),pelascolaborações,pelasrisadasepelo companheirismo. -
Graph Search Process in Social Networks and It's Challenges
Preeti Narooka et al | IJCSET(www.ijcset.net) | June 2016 | Vol 6, Issue 6, 228-232 Graph Search Process in Social Networks and it’s Challenges Ms. Preeti Narooka1, Dr. Sunita Chaodhary2 Ph. D Student, Banasthali University, Jaipur, India1 Former Associate Professor, Banasthali University, Jaipur, India 2 Abstract: - Social networking sites are grabbing attention of complex network where huge amount of data can be millions of users and it resulted into creation of humongous distribute and store easily. data on these networking sites. Number of users on any networking sites denotes the complexity and size of the data. Graph algorithm is the efficient tool which defines the These developments have thrown a challenge in front of relationships between all objects on social cloud. In today’s computer scientists to optimize the search operations on these scenario, users are increasing in Social Networks in leaps social networking sites. This paper outlines the Graph theory and bounds. With the increase of users, there is a rapid as a tool for search operation on social networking sites & for increment in number of objects on social graph, results in optimization of search graph operation map reducing exponential growth of the graph size [12]. Accessing useful technology is discussed. In this paper on one side, different information from exponentially growing graph in fast traditional system of social networking and graph algorithm are elaborated. On the other side, various application and manner is a very difficult challenging task. To provide different issues related to the graph algorithm and social solution for the aforesaid problem it is the need to optimize networking are discussed in detail. -
Unicorn: a System for Searching the Social Graph
Unicorn: A System for Searching the Social Graph Michael Curtiss, Iain Becker, Tudor Bosman, Sergey Doroshenko, Lucian Grijincu, Tom Jackson, Sandhya Kunnatur, Soren Lassen, Philip Pronin, Sriram Sankar, Guanghao Shen, Gintaras Woss, Chao Yang, Ning Zhang Facebook, Inc. ABSTRACT rative of the evolution of Unicorn's architecture, as well as Unicorn is an online, in-memory social graph-aware index- documentation for the major features and components of ing system designed to search trillions of edges between tens the system. of billions of users and entities on thousands of commodity To the best of our knowledge, no other online graph re- servers. Unicorn is based on standard concepts in informa- trieval system has ever been built with the scale of Unicorn tion retrieval, but it includes features to promote results in terms of both data volume and query volume. The sys- with good social proximity. It also supports queries that re- tem serves tens of billions of nodes and trillions of edges quire multiple round-trips to leaves in order to retrieve ob- at scale while accounting for per-edge privacy, and it must jects that are more than one edge away from source nodes. also support realtime updates for all edges and nodes while Unicorn is designed to answer billions of queries per day at serving billions of daily queries at low latencies. latencies in the hundreds of milliseconds, and it serves as an This paper includes three main contributions: infrastructural building block for Facebook's Graph Search • We describe how we applied common information re- product. In this paper, we describe the data model and trieval architectural concepts to the domain of the so- query language supported by Unicorn.