The document summarizes key differences between trends on the Chinese microblogging site Sina Weibo and the global social network Twitter. It finds that trends on Sina Weibo are formed almost entirely through repeated retweets of media like jokes, images and videos, whereas trends on Twitter more often relate to current events and news stories. It also observes that a higher percentage of top influencers on Sina Weibo are unverified individual accounts, compared to Twitter where more verified organizations and media outlets help set trends.
This document discusses the rise of user-generated content on the internet, known as Web 2.0. It notes that as technology prices drop, more people are able to create and share digital content like blogs, photos, and videos online. This user-generated content provides a wealth of data about people's everyday lives and social interactions. However, publishing personal content publicly exposes it to a large, invisible online audience in a way that challenges traditional notions of public and private. The document examines some of the theoretical implications of this shift and how social scientists can study online social interactions and their impact.
Social media? Get serious! Understanding the functional building blocks of so...Ian McCarthy
Traditionally, consumers used the Internet to simply expend content: they read it, they watched it, and they used it to buy products and services. Increasingly, however, consumers are utilizing platforms –— such as content sharing sites, blogs,
social networking, and wikis–—to create, modify, share, and discuss Internet content. This represents the social media phenomenon, which can now significantly impact a firm’s reputation, sales, and even survival. Yet, many executives eschew or ignore this form of media because they don’t understand what it is, the various forms it can take, and how to engage with it and learn. In response, we present a framework that defines
social media by using seven functional building blocks: identity, conversations, sharing, presence, relationships, reputation, and groups. As different social media activities are defined by the extent to which they focus on some or all of these blocks,
we explain the implications that each block can have for how firms should engage with social media. To conclude, we present a number of recommendations regarding how firms should develop strategies for monitoring, understanding, and responding to different social media activities.
Science and Social Media: The Importance of Being OnlineChristie Wilcox
This powerpoint was a part of a 2 hour workshop on social networking for scientists that was given at the 2012 NIH, NIGMS Fourth Biennial National IDeA Symposium of Biomedical Research Excellence (NISBRE).
Women are more active than men on social networks and blogs according to several studies. Research shows that women outnumber men on most social networks by about two to one. Younger women especially dominate the blogosphere and social media use. While men are more likely to use professional networks like LinkedIn, women are more engaged on personal networks focused on relationships and sharing content. Studies also found that women are more likely to spread information through their social networks and drive adoption of new websites or technologies through their connections. Targeting women can help websites and products go more viral.
Picturing the Social: Talk for Transforming Digital Methods Winter SchoolFarida Vis
This talk highlights the work of the Visual Social Media Lab and the Picturing the Social project. It summarises the key research questions and aims of the project. It highlights the value of interdisciplinarity and working closely with industry in this area. It also focuses on the way in which me might study different types of structures involved in the circulation and the scopic regimes that make social media images more or less visible. It also tries to unpack how we can start to think about APIs as 'method' and looks at the different ways in which we can get access to different kinds of social media image data. Both through public ('free') APIs and ('pay for') firehose data.
CSEAS: Cyber troop and computational propagandaIsmail Fahmi
International Seminar on “Cyber Troops and Computational Propaganda in the Indonesian Presidential Election 2019” at CSEAS, Kyoto University
Date: Saturday, July 20nd, 2019
Time: 16:00 -19:00
Venue: Kyoto University Inamori Memorial Hall, 2rd floor Seminar Room
Presenter: Ismail Fahmi (Drone Emprit & PT. Media Kernels Indonesia)
Moderator: Masaaki Okamoto (CSEAS Kyoto University)
ABSTRACT:
The last Indonesia’s 2019 presidential election shown a different landscape of cyber war compared to its previous 2014 presidential election. In 2014, the use of social media and online media to create propaganda during campaigns was relatively new. However, in 2019 the number of people engaged in the cyber war is significantly increased especially from the opposition side. The use of bots to manipulate public opinion by amplifying or combating political content, disinformation, hate speech, and junk news was also increased in both parties.
In this presentation I will present how cyber troops from both parties (incumbent and opposition) engaged cyber wars to win their campaign messages. Furthermore using Drone Emprit, our big data analytics tool for online media and social media, I will show how computational propaganda using sophisticated bots, patterns, and techniques to trick the social media platforms was engaged.
I also will explain our efforts using the Drone Emprit analytics, that regularly and continuously analyzed the conversation and shared our findings through article posts in social media and mainstream media during the campaign periods. Our purpose was to build public awareness about the situation of the cyber war in order to they can see how hidden teams conduct computational propaganda that was targeted to win their opinion.
At the end of the presentation, I will conclude with lesson learned from the Indonesia’s 2019 presidential election.
ESRC Research Methods Festival - From Flickr to Snapchat: The challenge of an...Farida Vis
From Flickr to Snapchat: The challenge of analysing images on social media. Presentation part of the 'Challenges/Opportunities of Using Social Media for Social Science Research' panel. 9th of July 2014
This document summarizes Farida Vis's use of social media to engage audiences for an academic conference on visual social media. It describes her strategy for promoting the conference months in advance on multiple social media platforms and tracking engagement. It also outlines her plan for sharing and curating content from the conference online in the following weeks to maximize engagement and create an archive.
This document discusses the rise of user-generated content on the internet, known as Web 2.0. It notes that as technology prices drop, more people are able to create and share digital content like blogs, photos, and videos online. This user-generated content provides a wealth of data about people's everyday lives and social interactions. However, publishing personal content publicly exposes it to a large, invisible online audience in a way that challenges traditional notions of public and private. The document examines some of the theoretical implications of this shift and how social scientists can study online social interactions and their impact.
Social media? Get serious! Understanding the functional building blocks of so...Ian McCarthy
Traditionally, consumers used the Internet to simply expend content: they read it, they watched it, and they used it to buy products and services. Increasingly, however, consumers are utilizing platforms –— such as content sharing sites, blogs,
social networking, and wikis–—to create, modify, share, and discuss Internet content. This represents the social media phenomenon, which can now significantly impact a firm’s reputation, sales, and even survival. Yet, many executives eschew or ignore this form of media because they don’t understand what it is, the various forms it can take, and how to engage with it and learn. In response, we present a framework that defines
social media by using seven functional building blocks: identity, conversations, sharing, presence, relationships, reputation, and groups. As different social media activities are defined by the extent to which they focus on some or all of these blocks,
we explain the implications that each block can have for how firms should engage with social media. To conclude, we present a number of recommendations regarding how firms should develop strategies for monitoring, understanding, and responding to different social media activities.
Science and Social Media: The Importance of Being OnlineChristie Wilcox
This powerpoint was a part of a 2 hour workshop on social networking for scientists that was given at the 2012 NIH, NIGMS Fourth Biennial National IDeA Symposium of Biomedical Research Excellence (NISBRE).
Women are more active than men on social networks and blogs according to several studies. Research shows that women outnumber men on most social networks by about two to one. Younger women especially dominate the blogosphere and social media use. While men are more likely to use professional networks like LinkedIn, women are more engaged on personal networks focused on relationships and sharing content. Studies also found that women are more likely to spread information through their social networks and drive adoption of new websites or technologies through their connections. Targeting women can help websites and products go more viral.
Picturing the Social: Talk for Transforming Digital Methods Winter SchoolFarida Vis
This talk highlights the work of the Visual Social Media Lab and the Picturing the Social project. It summarises the key research questions and aims of the project. It highlights the value of interdisciplinarity and working closely with industry in this area. It also focuses on the way in which me might study different types of structures involved in the circulation and the scopic regimes that make social media images more or less visible. It also tries to unpack how we can start to think about APIs as 'method' and looks at the different ways in which we can get access to different kinds of social media image data. Both through public ('free') APIs and ('pay for') firehose data.
CSEAS: Cyber troop and computational propagandaIsmail Fahmi
International Seminar on “Cyber Troops and Computational Propaganda in the Indonesian Presidential Election 2019” at CSEAS, Kyoto University
Date: Saturday, July 20nd, 2019
Time: 16:00 -19:00
Venue: Kyoto University Inamori Memorial Hall, 2rd floor Seminar Room
Presenter: Ismail Fahmi (Drone Emprit & PT. Media Kernels Indonesia)
Moderator: Masaaki Okamoto (CSEAS Kyoto University)
ABSTRACT:
The last Indonesia’s 2019 presidential election shown a different landscape of cyber war compared to its previous 2014 presidential election. In 2014, the use of social media and online media to create propaganda during campaigns was relatively new. However, in 2019 the number of people engaged in the cyber war is significantly increased especially from the opposition side. The use of bots to manipulate public opinion by amplifying or combating political content, disinformation, hate speech, and junk news was also increased in both parties.
In this presentation I will present how cyber troops from both parties (incumbent and opposition) engaged cyber wars to win their campaign messages. Furthermore using Drone Emprit, our big data analytics tool for online media and social media, I will show how computational propaganda using sophisticated bots, patterns, and techniques to trick the social media platforms was engaged.
I also will explain our efforts using the Drone Emprit analytics, that regularly and continuously analyzed the conversation and shared our findings through article posts in social media and mainstream media during the campaign periods. Our purpose was to build public awareness about the situation of the cyber war in order to they can see how hidden teams conduct computational propaganda that was targeted to win their opinion.
At the end of the presentation, I will conclude with lesson learned from the Indonesia’s 2019 presidential election.
ESRC Research Methods Festival - From Flickr to Snapchat: The challenge of an...Farida Vis
From Flickr to Snapchat: The challenge of analysing images on social media. Presentation part of the 'Challenges/Opportunities of Using Social Media for Social Science Research' panel. 9th of July 2014
This document summarizes Farida Vis's use of social media to engage audiences for an academic conference on visual social media. It describes her strategy for promoting the conference months in advance on multiple social media platforms and tracking engagement. It also outlines her plan for sharing and curating content from the conference online in the following weeks to maximize engagement and create an archive.
How information spreads on social networks when unexpected events occurFarida Vis
When unexpected events occur, information spreads on social networks through social dynamics. Trigger events that elicit an emotional response prompt users to share content. This impulse is validated when the content is seen as relevant to one's social circles and if others have already shared it, escalating its spread. However, during crises, misinformation also spreads rapidly online through images shared by locals and wider audiences, with the most visible information not always being the most valuable. It is important to examine less prominent sources to find useful information.
Fake News, Electronic Information and Transaction Law, and Civil Society Init...Ismail Fahmi
Ismail Fahmi presented on fake news, electronic information law, and civil society initiatives in Indonesia. He discussed how fake news has developed and spread through social media and alternative websites in Indonesia. Civil society groups like MAFINDO were formed to combat fake news through fact-checking, reporting hoaxes, and media literacy programs. However, media partisanship and clickbait headlines have also contributed to the spread of misinformation. The electronic information law has been used to target both anti-government and pro-government groups, but its broad scope has also led to persecution of legitimate critics. Moving forward, strengthening civil society, improving media standards, and increasing information literacy through education are needed to address the fake news issue in Indonesia
The evolution of research on social mediaFarida Vis
This document summarizes a presentation on the evolution of social media research. It discusses how early research focused on analyzing small datasets from platforms like Flickr and YouTube. Over time, as Twitter grew in popularity, researchers began analyzing larger Twitter datasets containing millions of tweets. However, these datasets still had limitations due to biases in the data available through APIs. The document also discusses critiques of "Big Data" approaches and the need for research to be question-driven rather than just analyzing available data. It emphasizes understanding the limitations of datasets and being transparent about how the data was collected and potential biases.
Analyzing social media may be a daunting task, given its overwhelming size and messy, unstructured nature. Further, for those new to analyzing social behavior in online systems, there are any number of pitfalls that make it challenging to find the meaning in the mess. The goal of this session is to provide practical tips for collecting and analyzing social media data.
Jacque lewis - Senior Project -w/o scriptJacque Lewis
This 12-minute mini-documentary explores whether social networks should enforce stricter regulations regarding social media harassment. The documentary features interviews with four professionals who discuss cyberbullying: Deborah Gonzalez, Jennifer Perry, Dr. Valerie Mason-John, and Shelia Mae. Through these interviews, the documentary seeks to answer its research question of whether social networks are responsible for enforcing their own rules against harassment and if those rules need to be stricter. Statistics about cyberbullying are also included throughout the documentary to provide context to the discussion. The documentary was created using Adobe Premiere to edit interview clips together with supplemental b-roll footage and was published on YouTube.
Social Networking And Hiv Aids Communications 01pete cranston
Presentation at the IAMCR conference on Social Networking and AIDS Communications by Pete Cranston. Commissioned by Communications and Social Change Consortium (www.cfsc.org) for AIDS2031 (www.aids2031.org)
This document discusses the impact of social media on youth. It begins with an abstract that outlines the objectives of a study conducted to analyze the effects of social media on youth education. 100 youth were surveyed about their favorite and most used social media platforms like Facebook, Skype, Twitter, YouTube, and Myspace. The document then provides background on the history of social media, beginning with early forms of communication like letters and the telegraph, and discusses how social media has evolved over the 20th century with technologies like email, blogs, MySpace, LinkedIn, YouTube, Facebook and Twitter. It outlines the main types of social media platforms used today, providing more detail on Facebook, email, and Twitter.
Week 6 slides from the class "Social Web 2.0" I taught at the University of Washington's Masters in Communication program in 2007. Most of the content is still very relevant today. Topics: Lightweight authoring, blogs, and wikis
Twitter analytics: some thoughts on sampling, tools, data, ethics and user re...Farida Vis
Keynote delivered at the SRA Social Media in Social Research conference, London, 24 June, 2013. The presentation highlights some thoughts on sampling, tools, data, ethics and user requirements for Twitter analytics, including an overview of a series of recent tools.
This presentation talks about basic principle and techniques of social media analytics. Covering basic data representation of social media, content analysis and network data analysis
Social Media Analysis: Present and Futurematthewhurst
Current social media analysis separates content and structure analysis, missing opportunities. A unified theory is needed to better analyze social media data by considering both content and structure together. While current applications focus on marketing, a broader business intelligence approach could expand the field. Developing richer models of business domains and processes would increase the actionability and market for social media analysis tools.
The document discusses how social media content from Twitter can be used to predict real-world outcomes. Specifically, it examines using tweets about movies to forecast box office revenues. The study shows that a simple model based on the rate tweets are created about movies can outperform market-based predictors for forecasting revenues. Sentiment analysis of tweets is also explored as a way to further improve predictions, especially after movies are released.
The document discusses Twitter, including its history and features. It provides examples of how organizations, local infrastructure organizations, and individuals can use Twitter. Key points include:
- Twitter allows users to share short messages or "tweets" of up to 140 characters and interact with other users.
- Many non-profits, local groups, and infrastructure organizations are using Twitter to share information, raise awareness, and engage their supporters.
- For individuals and organizations, Twitter can be useful for networking, getting news and information, and conversing with others in their field. However, it requires an ongoing commitment to see benefits.
Americans have drastically expanded their active communities online and offline. Their world is expanding and narrowing at the same time because of social media’s hyperlocalization quotient. And “cyberdisinhibition”—being more willing to behave online in ways they wouldn’t in person—has both emboldened users and led them to inappropriate behavior. These are among the findings from a nationwide study on social media conducted by Euro RSCG Worldwide. Despite buzz to the contrary, online social networking is having the effect of enhancing, not deteriorating, relationships among Americans. This new study, of 1,228 American social media users, found that by interacting through online media, consumers are more connected than ever.
The Benefits and Barriers for Social Media for ScientistsCraig McClain
Social media provides both benefits and challenges for scientists. It allows for quick connection and collaboration with other researchers, but does not directly correlate with increased citations. While it can help with outreach, communicating science to the public remains challenging. Many scientists see communication as filling knowledge deficits in the public, but this "deficit model" may not be effective. Effective social media use for outreach requires understanding audience and goals.
My Top Friend is Nike.
A short presentation on how-to integrate brands into social network services like facebook.
It gives an overview on Social Networks, explains the relation to Social Media and gives hands-on examples on howto integrate.
This is a copy of a presentation i did at ComputerSpace 2008 in Sofia, Bulgaria.
(c) http://die.socialisten.at
Contesting Language and Religious DiscourseIsmail Fahmi
This document summarizes Ismail Fahmi's presentation on contesting language and religious discourse in virtual communities in Indonesia's post-truth era. Fahmi analyzes big data on discussions of "Khilafah", "Kafir", and "Hijrah" on social media. For each term, he maps trends, networks, hashtags and memes to show polarization. Discussions of "Khilafah" involve pro-Khilafah, pro-government, and pro-opposition clusters politicizing the issue. The term "Kafir" is also highly polarized. Discussions of "Hijrah" and "Pemuda Hijrah" involve religious and opposing view
• Sosial media:
• Perannya semakin penting bagi publik dalam membagi dan mendapatkan informasi
terkait bantuan kemanusiaan.
• Lembaga bantuan kemanusiaan sudah aktif di media sosial, namun belum muncul peran sentralnya (top influencers) dalam percakapan dengan publik.
• Potensi dan Tantangan:
• Lembaga kemanusiaan memiliki relawan, informasi, dan data dari lapangan yang
uptodate;
• Di media sosial masih terlihat sendiri-sendiri (silos);
• Punya potensi besar dalam menggerakkan percakapan dan aksi berbasis data dan kisah di lapangan.
• Data philanthropy:
• Lembaga-lembaga kemanusiaan perlu merumuskan dan membangun “data
philanthropy” agar bisa memberi impact yang lebih sistemik dan berbasis data;
• Publik, institusi umum, pemerintah, dan lembaga kemanusiaan bisa menghadapi tantangan kemanusiaan bersama-sama dengan “data philanthropy”.
Online Search And Society: Could Your Best Friend Be Your Worst Enemy?Rachel Noonan
The document discusses how search engines have become one of the most disruptive technologies, with Google alone processing over 1.5 billion searches per day, and how search engines personalize results based on users' search histories and activities online, raising concerns about how this may influence society and individuals. It provides background on the rise of search engines and their evolution from basic web directories to personalized assistants that track extensive user data.
Artificial Inflation: The True Story of Trends in Sina WeiboDigicha
1) The document analyzes trends and trend-setters on Sina Weibo, China's largest microblogging platform.
2) It finds that retweets play a greater role in creating trends on Sina Weibo than on Twitter. A large percentage of trends are due to continuous retweets of a small number of fake accounts, artificially inflating certain posts.
3) These fake accounts were a small percentage of users but responsible for nearly half the retweets, influencing trending topics. Removing their tweets changed the evolution of trends.
Predicting the future with social media (Twitter y Box Office)Gonzalo Martín
This document examines using social media content from Twitter to predict real-world outcomes, specifically box office revenues for movies. It finds that the rate at which tweets are created about movies can be used to build a predictive model that outperforms market-based predictors. Sentiment analysis of tweets is also found to improve predictive power, with positive tweets encouraging viewership after a movie's release. The study analyzes attention and popularity trends on Twitter for movies as well as how sentiments influence people and box office performance.
How information spreads on social networks when unexpected events occurFarida Vis
When unexpected events occur, information spreads on social networks through social dynamics. Trigger events that elicit an emotional response prompt users to share content. This impulse is validated when the content is seen as relevant to one's social circles and if others have already shared it, escalating its spread. However, during crises, misinformation also spreads rapidly online through images shared by locals and wider audiences, with the most visible information not always being the most valuable. It is important to examine less prominent sources to find useful information.
Fake News, Electronic Information and Transaction Law, and Civil Society Init...Ismail Fahmi
Ismail Fahmi presented on fake news, electronic information law, and civil society initiatives in Indonesia. He discussed how fake news has developed and spread through social media and alternative websites in Indonesia. Civil society groups like MAFINDO were formed to combat fake news through fact-checking, reporting hoaxes, and media literacy programs. However, media partisanship and clickbait headlines have also contributed to the spread of misinformation. The electronic information law has been used to target both anti-government and pro-government groups, but its broad scope has also led to persecution of legitimate critics. Moving forward, strengthening civil society, improving media standards, and increasing information literacy through education are needed to address the fake news issue in Indonesia
The evolution of research on social mediaFarida Vis
This document summarizes a presentation on the evolution of social media research. It discusses how early research focused on analyzing small datasets from platforms like Flickr and YouTube. Over time, as Twitter grew in popularity, researchers began analyzing larger Twitter datasets containing millions of tweets. However, these datasets still had limitations due to biases in the data available through APIs. The document also discusses critiques of "Big Data" approaches and the need for research to be question-driven rather than just analyzing available data. It emphasizes understanding the limitations of datasets and being transparent about how the data was collected and potential biases.
Analyzing social media may be a daunting task, given its overwhelming size and messy, unstructured nature. Further, for those new to analyzing social behavior in online systems, there are any number of pitfalls that make it challenging to find the meaning in the mess. The goal of this session is to provide practical tips for collecting and analyzing social media data.
Jacque lewis - Senior Project -w/o scriptJacque Lewis
This 12-minute mini-documentary explores whether social networks should enforce stricter regulations regarding social media harassment. The documentary features interviews with four professionals who discuss cyberbullying: Deborah Gonzalez, Jennifer Perry, Dr. Valerie Mason-John, and Shelia Mae. Through these interviews, the documentary seeks to answer its research question of whether social networks are responsible for enforcing their own rules against harassment and if those rules need to be stricter. Statistics about cyberbullying are also included throughout the documentary to provide context to the discussion. The documentary was created using Adobe Premiere to edit interview clips together with supplemental b-roll footage and was published on YouTube.
Social Networking And Hiv Aids Communications 01pete cranston
Presentation at the IAMCR conference on Social Networking and AIDS Communications by Pete Cranston. Commissioned by Communications and Social Change Consortium (www.cfsc.org) for AIDS2031 (www.aids2031.org)
This document discusses the impact of social media on youth. It begins with an abstract that outlines the objectives of a study conducted to analyze the effects of social media on youth education. 100 youth were surveyed about their favorite and most used social media platforms like Facebook, Skype, Twitter, YouTube, and Myspace. The document then provides background on the history of social media, beginning with early forms of communication like letters and the telegraph, and discusses how social media has evolved over the 20th century with technologies like email, blogs, MySpace, LinkedIn, YouTube, Facebook and Twitter. It outlines the main types of social media platforms used today, providing more detail on Facebook, email, and Twitter.
Week 6 slides from the class "Social Web 2.0" I taught at the University of Washington's Masters in Communication program in 2007. Most of the content is still very relevant today. Topics: Lightweight authoring, blogs, and wikis
Twitter analytics: some thoughts on sampling, tools, data, ethics and user re...Farida Vis
Keynote delivered at the SRA Social Media in Social Research conference, London, 24 June, 2013. The presentation highlights some thoughts on sampling, tools, data, ethics and user requirements for Twitter analytics, including an overview of a series of recent tools.
This presentation talks about basic principle and techniques of social media analytics. Covering basic data representation of social media, content analysis and network data analysis
Social Media Analysis: Present and Futurematthewhurst
Current social media analysis separates content and structure analysis, missing opportunities. A unified theory is needed to better analyze social media data by considering both content and structure together. While current applications focus on marketing, a broader business intelligence approach could expand the field. Developing richer models of business domains and processes would increase the actionability and market for social media analysis tools.
The document discusses how social media content from Twitter can be used to predict real-world outcomes. Specifically, it examines using tweets about movies to forecast box office revenues. The study shows that a simple model based on the rate tweets are created about movies can outperform market-based predictors for forecasting revenues. Sentiment analysis of tweets is also explored as a way to further improve predictions, especially after movies are released.
The document discusses Twitter, including its history and features. It provides examples of how organizations, local infrastructure organizations, and individuals can use Twitter. Key points include:
- Twitter allows users to share short messages or "tweets" of up to 140 characters and interact with other users.
- Many non-profits, local groups, and infrastructure organizations are using Twitter to share information, raise awareness, and engage their supporters.
- For individuals and organizations, Twitter can be useful for networking, getting news and information, and conversing with others in their field. However, it requires an ongoing commitment to see benefits.
Americans have drastically expanded their active communities online and offline. Their world is expanding and narrowing at the same time because of social media’s hyperlocalization quotient. And “cyberdisinhibition”—being more willing to behave online in ways they wouldn’t in person—has both emboldened users and led them to inappropriate behavior. These are among the findings from a nationwide study on social media conducted by Euro RSCG Worldwide. Despite buzz to the contrary, online social networking is having the effect of enhancing, not deteriorating, relationships among Americans. This new study, of 1,228 American social media users, found that by interacting through online media, consumers are more connected than ever.
The Benefits and Barriers for Social Media for ScientistsCraig McClain
Social media provides both benefits and challenges for scientists. It allows for quick connection and collaboration with other researchers, but does not directly correlate with increased citations. While it can help with outreach, communicating science to the public remains challenging. Many scientists see communication as filling knowledge deficits in the public, but this "deficit model" may not be effective. Effective social media use for outreach requires understanding audience and goals.
My Top Friend is Nike.
A short presentation on how-to integrate brands into social network services like facebook.
It gives an overview on Social Networks, explains the relation to Social Media and gives hands-on examples on howto integrate.
This is a copy of a presentation i did at ComputerSpace 2008 in Sofia, Bulgaria.
(c) http://die.socialisten.at
Contesting Language and Religious DiscourseIsmail Fahmi
This document summarizes Ismail Fahmi's presentation on contesting language and religious discourse in virtual communities in Indonesia's post-truth era. Fahmi analyzes big data on discussions of "Khilafah", "Kafir", and "Hijrah" on social media. For each term, he maps trends, networks, hashtags and memes to show polarization. Discussions of "Khilafah" involve pro-Khilafah, pro-government, and pro-opposition clusters politicizing the issue. The term "Kafir" is also highly polarized. Discussions of "Hijrah" and "Pemuda Hijrah" involve religious and opposing view
• Sosial media:
• Perannya semakin penting bagi publik dalam membagi dan mendapatkan informasi
terkait bantuan kemanusiaan.
• Lembaga bantuan kemanusiaan sudah aktif di media sosial, namun belum muncul peran sentralnya (top influencers) dalam percakapan dengan publik.
• Potensi dan Tantangan:
• Lembaga kemanusiaan memiliki relawan, informasi, dan data dari lapangan yang
uptodate;
• Di media sosial masih terlihat sendiri-sendiri (silos);
• Punya potensi besar dalam menggerakkan percakapan dan aksi berbasis data dan kisah di lapangan.
• Data philanthropy:
• Lembaga-lembaga kemanusiaan perlu merumuskan dan membangun “data
philanthropy” agar bisa memberi impact yang lebih sistemik dan berbasis data;
• Publik, institusi umum, pemerintah, dan lembaga kemanusiaan bisa menghadapi tantangan kemanusiaan bersama-sama dengan “data philanthropy”.
Online Search And Society: Could Your Best Friend Be Your Worst Enemy?Rachel Noonan
The document discusses how search engines have become one of the most disruptive technologies, with Google alone processing over 1.5 billion searches per day, and how search engines personalize results based on users' search histories and activities online, raising concerns about how this may influence society and individuals. It provides background on the rise of search engines and their evolution from basic web directories to personalized assistants that track extensive user data.
Artificial Inflation: The True Story of Trends in Sina WeiboDigicha
1) The document analyzes trends and trend-setters on Sina Weibo, China's largest microblogging platform.
2) It finds that retweets play a greater role in creating trends on Sina Weibo than on Twitter. A large percentage of trends are due to continuous retweets of a small number of fake accounts, artificially inflating certain posts.
3) These fake accounts were a small percentage of users but responsible for nearly half the retweets, influencing trending topics. Removing their tweets changed the evolution of trends.
Predicting the future with social media (Twitter y Box Office)Gonzalo Martín
This document examines using social media content from Twitter to predict real-world outcomes, specifically box office revenues for movies. It finds that the rate at which tweets are created about movies can be used to build a predictive model that outperforms market-based predictors. Sentiment analysis of tweets is also found to improve predictive power, with positive tweets encouraging viewership after a movie's release. The study analyzes attention and popularity trends on Twitter for movies as well as how sentiments influence people and box office performance.
An experimental study in which we analyzed how individual twitter usage varies in conference settings.
Edgardo Vega, Ramanujam Parthasarathy, Josette Torres- Virginia Tech
The Networked Creativity in the Censored Web 2.0Weiai Wayne Xu
This document discusses a study analyzing the Twitter activities of Chinese users discussing and mobilizing around internet censorship. It provides background on China's censorship policies and innovations used to bypass them. The study uses Twitter data from 2014 and network, content, and demographic analyses to understand how users interact, tactics used, and characteristics of central users in the censorship discussion network. The goal is to understand how Web 2.0 platforms facilitate technological and political strategies to crowdsource responses to censorship.
Avinash Singh Bagri_Design and development of social media strategies in bank...Avinash Singh Bagri
This document is a project report submitted by Avinash Singh Bagri to IDRBT (Institute for Development and Research in Banking Technology) on the topic of "Design and Development of Social Media Strategies for Banking". The report was completed under the guidance of Dr. Shakti Mishra from May 13, 2013 to July 17, 2013. The report discusses the rise of social media and its various tools. It then focuses on how social media can be applied in different areas of banking like marketing, customer service, risk management and more. The report also examines some legal and governance issues around the use of social media in the banking sector.
The document discusses social media in China and how associations can leverage social media for awareness and engagement. It provides an overview of the China internet environment and popular social media platforms. Examples are given of how associations in different industries have used platforms like Sina Weibo, Youku, and Tianji to promote events, share updates, and interact with stakeholders. The document concludes with tips on how to get started with a social media strategy in China.
Social media has enabled crowd behavior to become independent of time and location. Examples include the 2011 Egyptian revolution which relied on Facebook and the 2011 London riots which spread via social media. Virtual crowds can belong to multiple online communities simultaneously through tools like Twitter, Facebook, and Reddit. These tools also allow information to spread virally very quickly with little direction. Businesses must track social media buzz using tools like Twitter, which allows public messaging and searching of tweets. Third party tools provide additional search capabilities and access to older tweets.
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1. What Trends in Chinese Social Media
Louis Yu Sitaram Asur Bernardo A. Huberman
Social Computing Lab Social Computing Lab Social Computing Lab
HP Labs HP Labs HP Labs
Palo Alto, California, USA Palo Alto, California, USA Palo Alto, California, USA
louis.yu@hp.com sitaram.asur@hp.com bernardo.huberman@hp.com
ABSTRACT millions of users all over the world. On the other hand, Sina
There has been a tremendous rise in the growth of online so- Weibo is a popular microblogging network in China which
cial networks all over the world in recent times. While some contains millions of users, almost all of whom are located in
networks like Twitter and Facebook have been well docu- China and post in the Chinese language.
mented, the popular Chinese microblogging social network In China, online social networks have become a major
Sina Weibo has not been studied. In this work, we examine platform for the youth to gather information and to make
the key topics that trend on Sina Weibo and contrast them friends with like-minded individuals [16]. In this regard, a
with our observations on Twitter. We find that there is a major point of interest is to examine the information that
vast difference in the content shared in China, when com- is propagated and the key trend-setters for this medium.
pared to a global social network such as Twitter. In China, There has been a lot of prior research done on the adaptation
the trends are created almost entirely due to retweets of of influence and evolution of trends in Western online social
media content such as jokes, images and videos, whereas on networks [2] [17] [20]. But, in contrast, Chinese social media
Twitter, the trends tend to have more to do with current has not been well-studied.
global events and news stories. In this paper, we analyze the evolution of Sina Weibo and
provide the first known in-depth study of trending topics
on a Chinese online microblogging social network. Our goal
Categories and Subject Descriptors is to discover important factors that determine popularity
H.4 [Information Systems Applications]: Miscellaneous; and influence in the context of Chinese social media. To
I.7.1 [Document and Text Processing]: Document and compare, we contrast them with corresponding ones from
Text Editing—languages Western social media (Twitter). We put emphasis on ex-
amining how trends are formed and what kind of sources
dominate the topics of discussion in Chinese social media.
General Terms First, we identify and collect the topics that are popular on
Measurement Sina Weibo over time. For each of these trending topics, we
analyze the characteristics of the users and the correspond-
Keywords ing tweets that are responsible for creating trends. We be-
lieve that this will give us a strong insight into the processes
social network; web structure analysis, China; social com- that govern social influence and adoption in China. To per-
puting form a comparison, we use similar trending topic data from
Twitter.
1. INTRODUCTION Our key findings are as follows. We observe that there
Social networks have made tremendous impact on on- are vast differences between the content that is shared on
line computing, by providing users opportunities to connect Sina Weibo when compared to Twitter. In China, people
with others and generate enormous content on a daily basis. tend to use Sina Weibo to share jokes, images and videos
The enormous user participation in these social networks and a significantly large percentage of posts are retweets.
is reflected in the incessant number of discussions, images, The trends that are formed are almost entirely due to the
videos, news and conversations that are constantly posted in repeated retweets of such media content. This is contrary to
social sites. Popular networks such as Facebook and Twit- what we observe on Twitter, where the trending topics have
ter are well-known globally and contain several hundreds of more to do with current events and the effect of retweets
is not as large. We also observe that there are more un-
verified accounts among the top 100 trend-setters on Sina
Permission to make digital or hard copies of all or part of this work for Weibo than on Twitter and most of the unverified accounts
personal or classroom use is granted without fee provided that copies are feature discussion forums for user-contributed jokes, images
not made or distributed for profit or commercial advantage and that copies and videos.
bear this notice and the full citation on the first page. To copy otherwise, or
republish, to post on servers or to redistribute to lists, requires prior specific
permission and/or a fee. 2. BACKGROUND AND RELATED WORK
The 5th SNA-KDD Workshop’11 (SNA-KDD’11), August 21, 2011, San
Diego CA USA.
Copyright 2011 ACM 978-1-4503-0225-8 ...$5.00.
2.1 Degree Distributions
2. There have been many experiments conducted for study- [21] [28]. Recently, Asur and others [2] have examined the
ing the structure of online social networks. In one compre- growth and persistence of trending topics on Twitter. They
hensive study, Mislove et al. [23] have presented a large- discovered that traditional media sources are important in
scale measurement study of online social networks such as causing trends on twitter. Many of the top retweeted arti-
Orkut, YouTube, and Flickr. Their results show that online cles that formed trends on Twitter were found to arise from
social networks follow the power-law in the in-degree and news sources such as the New York Times. In this work, we
out-degree distributions of user nodes. In other work, Ku- evaluate how the trending topics in China relate to the news
mar et al. [18] examine the linking structure of Flickr and media.
Yahoo!360 and report similar findings.
2.4 The Internet in China
2.2 Social Influence Studies The development of the Internet industry in China over
For many years the structure of various offline social net- the past decade has been impressive. According to a survey
works has been studied by sociologists (see [15] [23] [6] for from the China Internet Network Information Center (CN-
surveys). Researchers have also analyzed the structure of NIC), by July 2008, the number of Internet users in China
various Chinese offline social networks [4] [25] [12] [5] [7]. In has reached 253 million, surpassing the U.S. as the world’s
social network analysis, social influence refers to the concept largest Internet market [9]. Furthermore, the number of In-
of people modifying their behavior to bring them closer to ternet users in China as of 2010 was reported to be 420
the behavior of their friends. million.
Social influence has been studied in a vast array of social Despite this, the fractional Internet penetration rate in
networks involving various foci such as interests and per- China is still low. The 2010 survey by CNNIC on the In-
sonal habits [22] [13] [26]. Xu et al. [30] have looked at ternet development in China [10] reports that the Internet
the adaptation of aggressive behaviors in a social network of penetration rate in the rural areas of China is on average
kindergarden children in China. As a method of controlling 5.1%. In contrast, the Internet penetration rate in the ur-
aggression, teachers in China tend to put aggressive chil- ban cities of China is on average 21.6%. In metropolitan
dren in a peer group with non-aggressive children. Xu et cities such as Beijing and Shanghai, the Internet penetra-
al. [30] have found that over time friendships can be formed tion rate has reached over 45%, with Beijing being 46.4%
between aggressive children and non-agressive children. For and Shanghai being 45.8% [10].
the aggressive children who are group members, intra-group According to the survey by CNNIC in 2010 [9], China’s
friendships moderated their aggressive behavior. cyberspace is dominated by urban students between the age
Agarwal et al. [1] have examined the problem of identi- of 18–30 (see Figure 1 and Figure 2, taken from [9]).
fying influential bloggers in the blogosphere. They discov-
ered that the most influential bloggers were not necessarily
the most active. Backstrom et al. [3] have examined the
characteristics of membership closure in LiveJournal. and
Crandall et al. [11], the adaptation of influences between
editors of Wikipedia articles. On Twitter, Cha et al. [8]
have performed a comparison of three different measures of
influence - indegree, retweets and user mentions. Based on
this, they hypothesized that the number of followers may
not a good measure of influence. This was corroborated by
Romero and others [24] who presented a novel influence mea-
sure that takes into account the passivity of the audience in
the social network. They measured retweets on Twitter and
found that passivity was a major factor when it came to for-
warding. They also demonstrated with empirical evidence
that the number of followers is a poor measure of influence. Figure 1: Age Distribution of Internet Users in
There are only a few studies of social influence in Chi- China
nese online social networks. Jin [16] has studied the Chinese
online Bulletin Board Systems (BBS), and provided obser- The Government plays an important role in fostering the
vations on the structure and interface of Chinese BBS and advance of the Internet industry in China. Tai [31] points
the behavioral patterns of its users. Xin [29] has conducted out the four major stages of Internet development in China,
a survey on BBS’s influence on the University students in “with each period reflecting a substantial change not only
China and their behavior on Chinese BBS. Yu et al. [32] in technological progress and application, but also in the
has looked at the adaptation of interests such as books, Government’s approach to and apparent perception of the
movies, music, events and discussion groups on Douban, an Internet.”
online social network frequently used by the youth in China.
Douban provides users with review and recommendation ser- 1. The first phase was between 1986–1992, when Internet
vices for movies, books, music and events. It is also the applications were limited to the use of emails among a
largest online media database and one of the largest online handful of computer research labs in China.
communities in China. 2. The second phase was between 1992–1995, the Chi-
nese Government proposed several large scale network
2.3 Trends on Twitter projects and built a national information network in-
There are various studies on trends on Twitter [14] [19] frastructure.
3. the huge quantity of BBS posts and blog ar-
ticles is far beyond that of any other country.
China’s websites attach great importance to pro-
viding netizens with opinion expression services,
with over 80% of them providing electronic bul-
letin service. In China, there are over a million
BBSs and some 220 million bloggers. According
to a sample survey, each day people post over
three million messages via BBS, news commen-
tary sites, blogs, etc., and over 66% of Chinese
netizens frequently place postings to discuss var-
ious topics, and to fully express their opinions
and represent their interests. The new applica-
tions and services on the Internet have provided
a broader scope for people to express their opin-
ions. The newly emerging online services, includ-
ing blog, microblog, video sharing and social net-
working websites are developing rapidly in China
and provide greater convenience for Chinese cit-
izens to communicate online. Actively partici-
pating in online information communication and
content creation, netizens have greatly enriched
Internet information and content.
Figure 2: The Occupation Distribution of Internet
Users in China
3. SINA WEIBO
From the above motivation, we think it is interesting to
3. The third phase was between 1995–1997. The Chinese look at how trends start and evolve in various Chinese on-
Government stepped up its effort in building the in- line social networks and to analyze the characteristics of
formation network infrastructure, hoping that the IT trend-setters determining if they represent Government or-
industry would yield significant benefits to the nation’s ganizations, commercial organizations, the media, or indi-
economy. Meanwhile, the Government started to im- viduals. We choose to analyze the characteristics of trends
plement a variety of technological and policy control and trend-setters on Sina Weibo. Sina Weibo was launched
mechanisms to regulate the safe flow of the information by the Sina corporation, China’s biggest web portal, in Au-
on the Internet. gust 2009. On July 2009, the Chinese Government blocked
4. The fourth phase started from 1998 and continues to the access to Twitter and Fanfou, the then leading Twit-
the present, during which time the Internet has become ter clone, in China. Internet companies such as Sina and
a powerful medium in the Chinese society. Tencent started offering microblog services to their users in
mainland China. According to the Sina corporation annual
According to The Internet in China 1 released by the In- report 3 , the Weibo microblog now has more than 50 million
formation Office of the State Council of China: active users per day, and 10 million newly registered users
per month.
The Chinese government attaches great impor- While both Twitter and Sina Weibo enable users to post
tance to protecting the safe flow of Internet in- messages of up to 140 characters, there are some differences
formation, actively guides people to manage web- in terms of the functionalities offered. We give a brief intro-
sites in accordance with the law and use the In- duction of Sina Weibo’s interface and functionalities.
ternet in a wholesome and correct way.
3.1 User Profiles
2.5 Chinese Online Social Networks A user profile on Sina Weibo displays the user’s name, a
Online social networks are a major part of the Chinese brief description of the user, the number of followers and
Internet culture [16]. Netizens2 in China organize them- followees the user has, and the number of tweets the user
selves using forums, discussion groups, blogs, and social net- made. A user profile also displays the user’s recent tweets
working platforms to engage in activities such as exchanging and retweets.
viewpoints and sharing information [16]. According to The Similar to Twitter, there are two types of user accounts on
Internet in China: Sina Weibo, regular user accounts and verified user accounts.
A verified user account typically represents a well known
Vigorous online ideas exchange is a major char- public figure or organization in China. Sina has reported
acteristic of China’s Internet development, and in the annual report that it has more than 60,000 verified
accounts consisting of celebrities, sports stars, well known
1
“The Internet in China” by the Information Office of the organizations (both Government and commercial) and other
State Council of the People’s Republic of China is available
at http://www.scio.gov.cn/zxbd/wz/201006/t667385.htm 3
The Sina corporation annual report 2011 is avail-
2
A netizen is a person actively involved in online communi- able (in Chinese) at http://tech.sina.com.cn/i/2010-11-
ties [27]. 16/10314870771.shtml
4. VIPs.
3.2 The Content of Tweets on Sina Weibo
There is an important difference in the content of tweets
between Sina Weibo and Twitter. While Twitter users can
post tweets consisting of text and links, Sina Weibo users can
post messages containing text, pictures, videos and links.
Figure 3 illustrates some messages with embedded pictures
and videos on Sina Weibo.
Figure 4: An Example of Comments and Retweets
(Translations of the Tweets Omitted)
illustrates the list of hourly trending keywords (with transla-
tions). This is similar to Twitter, which also presents a con-
stantly updated list of trending topics, which are keywords
that are most frequently used in tweets over that period.
Figure 3: An Example of Embedded Videos and Pic-
tures (Translations of the Tweets Omitted)
3.3 Retweets and Comments
Twitter users can address tweets to other users and can
mention others in their tweets [13]. A common practice
on Twitter is “retweeting”, or rebroadcasting someone else’s
messages to one’s followers. The equivalent of a retweet on
Sina Weibo is instead shown as two two amalgamated en-
tries: the original entry and the current user’s actual entry
which is a commentary on the original entry (see Figure 4).
Sina Weibo also has a functionality absent from Twitter:
the comment. When a Weibo user makes a comment, it is Figure 5: The List of Hourly Trending Keywords
not rebroadcasted to the user’s followers. Instead, it can (with Translations)
only be accessed under the original message.
Figure 4 illustrates two example tweets on Sina Weibo. We monitored the list of hourly trending keywords every
The first is an original tweet made by a user, we can see that hour for 30 days and retrieved every new keywords appeared
the retweeting and commenting buttons are listed under the in the list. We retrieved in total 4411 new trending keywords
tweet. The second is a retweet, we can see that the original over the 30 days observation period.
message is retweeted 62 times and commented 10 times by To compare with Twitter, we obtained 16.32 million tweets
other users. on 3361 different trending topics over 40 days using the
Twitter Search API.
3.4 Trending keywords
Sina Weibo offers a list of 50 keywords that appeared most 4. EXPERIMENTS AND RESULTS
frequently in users’ tweets over the past hour. They are First, we calculated the distributions for the number of
ranked according to the frequency of appearances. Figure 5 tweets and topics in our dataset. Figure 6 a) illustrates
5. Table 1: Top 20 Retweeted Users in At Least 10 Trending Topics
ID Author Description (Translated) Verified Account Retweets Tweets Topics Retweet-Ratio
1 1757128873 Urban Fashion Magazine Yes 1194999 37 12 99583.25
2 1643830957 Fashion Brand VANCL Yes 849404 21 13 65338.77
3 1670645393 Online Travel Magazine Yes 127737 123 21 57987.48
4 1992523932 Gourmet Factory No 553586 86 12 46132.17
5 1735618041 Horoscopes No 1545955 101 38 40683.13
6 1644395354 Silly Jokes No 3210130 258 81 39631.23
7 1843443790 Good Movies No 1497968 140 38 39420.21
8 1644572034 Wonderful Quotes No 602528 39 17 35442.82
9 1674242970 Global Music No 697308 116 22 31695.81
10 1713926427 Funny Jokes Countdown No 3667566 438 121 30310.46
11 1657430300 Creative Ideas No 742178 111 25 29687.12
12 1195230310 Famous Chinese singer Yes 284600 25 10 28460
13 1750903687 Good Music No 323022 52 12 26918.5
14 1757353251 Movie Factory No 1509003 230 59 25576.32
15 1644570320 Strange Stories No 1668910 250 66 25286.52
16 1802393212 Beautiful Pictures No 435312 33 18 24184
17 1920061532 Global Music No 432444 65 18 24024.67
18 1644574352 Female Fashion No 809440 87 34 23807.06
19 1780417033 Useful Tips No 735070 153 31 23711.94
20 1644394154 Funny Quizzes No 589477 77 25 23579.08
the distributions for the number of users (Y-axies) with a Author Retweets Topics Retweet-Ratio
certain number of tweets (X-axis) in our list of trending vovo panico 11688 65 179.81
topics; Figure 6 b) illustrates the distribution for the number cnnbrk 8444 84 100.52
of users (Y-axis) whose tweets appear in numbers of topics keshasuja 5110 51 100.19
(X-axis). As we can observe from the figure, both these LadyGonga 4580 54 84.81
distributions follow the power law. BreakingNews 8406 100 84.06
MLB 3866 62 62.35
4.1 Trend-setters on Sina Weibo nytimes 2960 59 50.17
One of the main forms of information propagation in so- HerbertFromFG 2693 58 46.43
cial networks such as Twitter and Sina is through retweets. espn 2371 66 35.92
When people find a tweet interesting either due to the con- globovision 2668 75 35.57
tent or the source, they forward it to their followers. huffingtonpost 2135 63 33.88
For every new trending keyword we retrieved the most skynewsbreak 1664 52 32
retweeted tweets in the past hour and compiled a list of el pais 1623 52 31.21
most retweeted users. Table 1 illustrates the top 20 most stcom 1255 51 24.60
retweeted authors appearing in at least 10 trending topics la patilla 1273 65 19.58
each. We define an author’s retweet ratio as the number reuters 957 57 16.78
of times the authors’ tweets are retweeted divided by the WashingtonPost 929 60 15.48
number of trending topics these tweets appeared in. bbcworld 832 59 14.10
For each author we have included the ID of the user ac- CBSnews 547 56 9.76
count (ID), a brief translation of the description of the au- TelegraphNews 464 79 5.87
thors (author description), whether it is a verified account, tweetmeme 342 97 3.52
the number of tweets the author made in the trending topics nydailynews 173 51 3.39
(tweets), the number of times these tweets are retweeted, the
number of topics the authors’ tweets appeared in (topics), Table 2: Top Retweeted Users on Twitter contribut-
and finally, the influential authors are ranked according to ing to at least 50 trending topics each
their retweet ratios.
4.1.1 Authors to contribute jokes or stories. Once they are posted, other
From Table 1 we observed that only 4 out of the top 20 followers tend to retweet them frequently.
influential authors were verified accounts. The 4 verified We further inspect one of the accounts: ID 1644395354
accounts represent an urban fashion magazine, a fashion (see Figure 7); This account focuses on posting tweets about
brand, an online travel magazine, and a Chinese celebrity. jokes. We see from the description of the user that this
The other 16 influential authors are unverified accounts. account welcomes submission from followers. Followers of
They all seem to have a strong focus on collecting user- this account can email jokes to the account and the account
contributed jokes, movie trivia, quizzes, stories and so on. administrator will post them. From Figure 7 we also see a
When we further inspected these accounts, we discovered contribution from a follower.
that these accounts seem to operate as discussion and shar- The corresponding most retweeted users for trending top-
ing platforms. The users who follow these accounts tend ics on Twitter is shown in Table 2. In this case, the list is
7. Author Followees Followers
vovo panico 1069 154589
cnnbrk 41 4380908
keshasuja 0 88
LadyGonga 37 136433
BreakingNews 382 2570662
MLB 18829 1237615
nytimes 465 3250977
HerbertFromFG 763 23318
espn 286 1326168
globovision 3582 753440
huffingtonpost 4684 1042330
skynewsbreak 5 198349
el pais 46226 572260
stcom 12 59763
la patilla 51 306965
reuters 603 724204
WashingtonPost 284 458721
bbcworld 20 796009
CBSnews 122 1716649
TelegraphNews 238 38599
Table 4: Follower/Followee relationships for Top
Retweeted Twitter Users
trending topics. While retweets do contribute to making a
topic trend on Twitter, their effect is not so large.
Figure 7: An Illustration of an User Account on Sina 4.1.3 Embedded Images, Videos and Links in Tweets
Weibo For the list of trend-setters on Sina Weibo (Table 1), we
also examine the content of their tweets that appeared in the
trending topics. Table 3 illustrates the percentage of these
dominated by popular news sources such as CNN, the New users’ tweets which included images, videos, and links. We
York Times and ESPN. A large percentage of the topics that observe that a large percentage of the tweets of these users
trended accordingly dealt with events in the news. This in- include an embedded image, and many tweets included an
dicates that Twitter users are more attuned to news events embedded video or a link. On the other hand, Twitter users
than Sina Weibo users and amplify such articles through post links in only 17.6% of the tweets on trending topics.
the medium of Twitter. On the other hand, the consistent This is again demonstrative of the type of content that is
trend-setters on Sina Weibo are not media organizations. shared in these two social media services.
Instead they are unverified accounts acting as discussion fo-
rums and a platform for users to share funny pictures, jokes, 4.1.4 Follower Relationships
and stories. We observe that none of the unverified accounts For each of the influential authors, we looked at the num-
in Table 1 are personal accounts, with only 1 out of 4 verified ber of followers and followees they have, and the total num-
accounts (in the top 20) belonging to a media organization. ber tweets they have made since their accounts are activated
This represents an important contrast in the use of these (Table 3). We discovered that most of the influential authors
media, with Chinese users being more inclined to share and have more followers than followees. We hypothesize that
propagate trivial content than the Twitter users. these influential authors do not actively seek out accounts
to follow. It is their content which attracts other users to
4.1.2 Retweets follow them. Interestingly, we found this to be true on Twit-
When we consider the ratio of retweets, we once again ter as well (shown in Table 4), with the top retweeted users
observe a strong contrast with Twitter. The number of having very skewed follower/followee ratios.
retweets that authors get on Sina Weibo are several orders
of magnitude greater than the retweets for the trending top- 4.1.5 Verified Accounts
ics on Twitter, although they contribute to fewer topics. When we considered the top 100 trend-setters, we found
This implies that the topics are trending mainly because that only 23 were verified accounts. The descriptions of
of some content that has been retweeted many times. The these 23 are shown in Table 5. We observed the verified
T weets column in Table 1 gives the unique tweets that have accounts are of celebrities, newspapers, magazines and a few
been retweeted. We can observe that the rate at which they other media sources.
have been retweeted is phenomenal. For example, the top
retweeted user posted 37 tweets which were totally retweeted 4.2 Random Profile Analysis
1194999 times. The overall retweet percentage was around From the above analyses, we observe that the Sina Weibo
62% for the trending topics. In contrast, for Twitter trends, user accounts whose tweets are retweeted frequently and ap-
the retweets form only 31% of the overall tweets for the pear in multiple trending topics over time are mostly estab-
8. Figure 8: The Distribution for the Percentage of Tweets that are a) Retweets and b) include images
Figure 9: The Distribution for the Percentage of Tweets that include a) Videos and b) Links
lished for discussion and image/video sharing purposes. Fol- tweets by our 1732 random users are retweets, and over half
lowers use these accounts to share interesting stories, jokes, of the tweets include an embedded image. Figure 8 a) illus-
and pictures. We hypothesize that in general, users of Sina trates the histogram for the number of users with a certain
Weibo tend to retweet information more often than Twit- percentage of tweets which are retweets. We see that the dis-
ter users. We also hypothesize that a high percentage of tributions for the number of users are fairly even throughout
these users’ tweets tend to include an image or a video for all the percentages and is especially high around 45%, 60%,
illustration purposes. 70% and 80%.
To verify the above hypothesis, we selected 1732 random Content: Figure 8 b) illustrates the histogram for the
users on Sina Weibo. For each user, we retrieved his/her last number of users with a certain percentage of tweets which
100 tweets and analyzed the percentage of the tweets which include an embedded image. We see that the distribution
include images, videos, links and the percentage of tweets for the number of users peak at around 55% and 80% while
that are retweets. remain low below 40% and above 85%. Figure 9 a) and 9
Retweets: We find that on average 50.24% of the tweets b) illustrates the histograms for the number of users with
are retweets (49,76% of the tweets are original tweets), 56.43% a certain percentage of tweets which include a video or a
of the tweets include an embedded image (43.57% of the link. We see that both distributions peaked at 5% and then
tweets do not), only 5.57% of the tweets include an embed- diminish quickly after. In the case of twitter, all forms of
ded video (94.43% did not) and 8.03% of the tweets include media are shared through the use of hyperlinks. It has been
a link (91.94% did not). We observe that over half of the shown in [24] that URLs form 1/15th (6.6%) of all twitter
9. Rank ID Description Sociological Review, 62(3):366–385, 1997.
1 1757128873 Fashion Web Magazine [5] Y. Bian, R. Breiger, D. Davis, and J. Galaskiewicz.
2 1643830957 Fashion Brand Occupation, class, and social networks in urban china.
2 1670645393 Travel Web Magazine Social Forces, 83(4):1443–1468, 2005.
12 1195230310 Celebrity [6] M. Buchanan. Nexus: Small Worlds and the
21 1740006601 Celebrity Groundbreaking Theory of Networks. W. W. Norton &
25 1730380283 Game Discussion Forum Company, May 2003.
26 1760945071 Chinese Groupon
[7] P. J. Carrington, J. Scott, and S. Wasserman, editors.
42 1322920531 Celebrity
Models and Methods in Social Network Analysis.
43 1771665380 Record Label
Cambrige University Press, 2005.
46 1266321801 Celebrity
[8] M. Cha, H. Haddadi, F. Benevenuto, and K. P.
48 1883881851 Organization (NBA China)
Gummadi. Measuring User Influence in Twitter: The
58 1698229264 Music Web Magazine
Million Follower Fallacy. In Fourth International
62 1642591402 Sina Entertainment
AAAI Conference on Weblogs and Social Media, May
70 1743374541 Pictures Discussion Forum
2010.
71 1618051664 Sina News
74 1653689003 Newspaper [9] CNNIC. The 21st statistics report on the internet
75 1640601392 Sina Video development in china (in chinese), 2010.
82 1195031270 Celebrity [10] CNNIC. Survey report on internet development in
83 1835254597 Music Web Magazine rural china (in chinese), 2010.
84 1830442653 Music Web Magazine [11] D. Crandall, D. Cosley, D. Huttenlocher, J. Kleinberg,
95 1765148101 Sina Fashion and S. Suri. Feedback effects between similarity and
96 1258256457 Celebrity social influence in online communities. In Proceedings
100 1596329427 Celebrity of the 14th ACM SIGKDD international conference on
Knowledge discovery and data mining, pages 160–168.
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influence of relational demography and guanxi: the
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