Congratulations to CASCI alumnus Dr. Ahmed Abdeen Hamed who was recognized by FastCompany magazine, among the most creative people in the world, in 2016, for his research publication entitled: Twitter K-H networks in action: Advancing biomedical literature for drug search.Dr. Hamed completed his Computer Science MS degree at Indiana University in May 2005 and joined our Complex Networks & Systems track of the PhD in Informatics in the Fall of 2008. For personal reasons, he finished his PhD at the University of Vermont, but started his research in biomedical text mining with the CASCI group.
For the past four years, researchers at the Center for Complex Networks and Systems Research at the Indiana University School of Informatics and Computing have been studying the ways in which information spreads on social media networks such as Twitter. This basic research project is federally funded, like a large percentage of university research across the country.
The project, informally dubbed “Truthy,” makes use of complex computer models to analyze the sharing of information on social media to determine how popular sentiment, user influence, attention, social network structure, and other factors affect the manner in which information is disseminated. Additionally, an important goal of the Truthy project is to better understand how social media can be abused.
Since 25 Aug 2014, when a first misleading article was posted on a conservative blog, the Truthy project has come under criticism from some, including The Kelly File and Fox and Friends broadcasts by Fox News on 26 and 28 Aug 2014, who have misrepresented its goals. Contrary to these claims, the target is the study of the structural patterns of information diffusion. For example, an email sent simultaneously to a million addresses is likely spam, even if we have no automatic way to determine whether its content is true or false. The assumption behind the Truthy effort is that an understanding of the spreading patterns may facilitate the identification of abuse, independent from the nature or political color of the communication.
While the Truthy platform provides support to study the evolution of communication in all portions of the political spectrum, it is not informed by political partisanship. The machine learning algorithms used to identify suspicious patterns of information diffusion are entirely oblivious to the possibly political partisanship of the messages.
Timeline and updates:
8/28/2014: Despite the clarifications in this post, Fox News and others continued to perpetrate their attacks to our research project and to the PI personally. Their accusations are based on false claims, supported by bits of text and figures selectively extracted from our writings and presented completely out of context, in misleading ways. None of the researchers were contacted for comments before these outlandish conspiracy theories were aired and published. There is a good dose of irony in a research project that studies the diffusion of misinformation becoming the target of such a powerful disinformation machine. (The video of the first segment on “The Kelly File” with misinformation about our project was later removed from the Fox News website.)
9/3/2014: David Uberti wrote an accurate account of recent events in Columbia Journalism Review.
10/18/2014: Unfortunately, the smear campaign against our research project continues, with unsupported allegations echoed in an misleading op-ed by FCC Commissioner Ajit Pai, who did not contact any of the researchers with questions about the accuracy of his allegations.
10/22/2014: Amid news reports that the chairman of the House Science, Space and Technology Committee initiated an investigation into the NSF grant supporting our project, read our interview in the Washington Post’s Monkey Cage setting the record straight about our research.
10/24/2014: Fox News and FCC Commissioner Pai continue to spread disinformation about our research. (The video of the interview about our project, to which we were not invited, was later removed from the Fox News website.)
11/3/2014: Jeffrey Mervis covers the controversy about this project in Science. We also provided additional information about our research in a slide deck embedded at the bottom of this post.
11/4/2014: Five leading computing societies and associations (CRA, ACM, AAAI, USENIX, and SIAM) wrote a joint letter to the chairman and the committee ranking member of the House Committee on Science, Space, and Technology expressing their concern over mischaracterizations of our research.
11/7/2014: Over the past few days we have seen more coverage in Computer World, The Hill, Information Week, and Science about the reactions of the computing and science communities to the Truthy controversy.
11/11/2014: The House Science Committee Chairman sent a letter to the director of the NSF on November 10, stating that our grant “was intended to create standards for online political discussion” and that a web service developed under the grant “targeted conservative social media messages.” These allegations are false, as we have explained in this post, in the slides embedded below, and in our publications — including the one quoted in the Chairman’s letter. On the same day, the Association of American Universities released a statement on the grant inquires by the House Science Committee.
11/21/2014: False rumors about our research continue to be spread. Some of the questions we have received suggested that our two separate project and demo websites were generating confusion, so we merged them into a redesigned research website with information and highlights about the research project, publications, demos, data, etc.
11/25/2014: Rep. Johnson and Rep. Lofgren, respectively ranking member and member of the House Committee on Science, write a letter to the committee chairman, Rep. Smith, in response to his accusations.
Facts about Truthy:
- Truthy is an informal nickname associated with a research project of the Center for Complex Networks and Systems Research at the IU School of Informatics and Computing. The project aims to study how information spreads on social media, such as Twitter.
- The project has focused on domains such as news, politics, social movements, scientific results, and trending social media topics. Researchers develop theoretical computer models and validate them by analyzing public data, mainly from the Twitter streaming API.
- Social media posts available through public APIs are processed without human intervention or judgment to visualize and study the spread of millions of memes. We aim to build a platform to make these analytic tools easily accessible to social scientists, reporters, and the general public.
- An important goal of the project is to help mitigate misuse and abuse of social media by helping us better understand how social media can be potentially abused. For example: when social bots are used to create the appearance of human-generated communication (hence the name “truthy”). We study whether it is possible to automatically differentiate between organic content and so-called “astroturf.”
- Examples of research to date include analyses of geographic and temporal patterns in movements like Occupy Wall Street, societal unrest in Turkey, the polarization of online political discourse, the use of social media data to predict election outcomes and stock market movements, and the geographic diffusion of trending topics.
- On the more theoretical side, we have studied how individuals’ limited attention span affects what information we propagate and what social connections we make, and how the structure of social networks can help predict which memes are likely to become viral.
- Hundreds of researchers across the U.S. and the world are studying similar issues based on the same data and with analogous goals — these topics were studied well before the advent of social media. In the US these research efforts are supported not only by the NSF but also by other federal funding agencies such as DoD, DARPA, and IARPA.
- The results of our research have been covered widely in the press, published in top peer-reviewed journals, and presented at top conferences worldwide. All papers are publicly available.
Finally, the Truthy research project is not and never was:
- a political watchdog
- a database to be used by the federal government to monitor the activities of those who oppose its policies
- a government probe of social media
- an attempt to suppress free speech or limit political speech or develop standards for online political speech
- a way to define “misinformation”
- a partisan political effort
- a system targeting political messages and commentary connected to conservative groups
- a mechanism to terminate any social media accounts
- a database tracking hate speech
The DESPIC team at the Center for Complex Systems and Networks Research (CNetS) presented a demo of a new tool named BotOrNot at a DoD meeting held in Arlington, Virginia on April 23-25, 2014. BotOrNot (truthy.indiana.edu/botornot) is a tool to automatically detect whether a given Twitter user is a social bot or a human. Trained on Twitter bots collected by our lab and the infolab at Texas A&M University, BotOrNot analyzes over a thousand features from the user’s friendship network, content, and temporal information in real time and estimates the degree to which the account may be a bot. In addition to the demo, the DESPIC team (including colleagues at the University of Michigan) presented several posters on Scalable Architecture for Social Media Observatory, Meme Clustering in Streaming Data, Persuasion Detection in Social Streams, High-Resolution Anomaly Detection in Social Streams, and Early Detection and Analysis of Rumors. See more coverage of BotOrNot on PCWorld, IDS, BBC, Politico, and MIT Technology Review.
Congratulations to Lilian Weng, who successfully defended her Informatics PhD dissertation titled Information diffusion on online social networks. The thesis provides insights into information diffusion on online social networks from three aspects: people who share information, features of transmissible content, and the mutual effects between network structure and diffusion process. The first part delves into the limited human attention. The second part of Dr. Weng’s dissertation investigates properties of transmissible content, particularly into the topic space. Finally, the thesis presents studies of how network structure, particularly community structure, influences the propagation of Internet memes and how the information flow in turn affects social link formation. Dr. Weng’s work can contribute to a better and more comprehensive understanding of information diffusion among online social-technical systems and yield applications to viral marketing, advertisement, and social media analytics. Congratulations from her colleagues and committee members: Alessandro Flammini, YY Ahn, Steve Myers, and Fil Menczer!
Findings by CNetS researchers on social media indicators of election results received significant coverage in the national press. The paper More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior by Joseph Digrazia, Karissa McKelvey, Johan Bollen, and Fabio Rojas was presented at the 2013 Meeting of the American Sociological Association in NYC. It was covered by NPR, The Wall Street Journal, MSNBC, C-SPAN, The Washington Post, The Atlantic, and many other media.
Congratulations to Przemyslaw Grabowicz, Luca Aiello, and Fil Menczer for winning the WICI Data Challenge. A prize of $10,000 CAD accompanies this award from the Waterloo Institute for Complexity and Innovation at the University of Waterloo. The Challenge called for tools and methods that improve the exploration, analysis, and visualization of complex-systems data. The winning entry, titled Fast visualization of relevant portions of large dynamic networks, is an algorithm that selects subsets of nodes and edges that best represent an evolving graph and visualizes it either by creating a movie, or by streaming it to an interactive network visualization tool. The algorithm is deployed in the movie generation tool of the Truthy system, which allows users to create, in near-real time, YouTube videos that illustrate the spread and co-occurrence of memes on Twitter. Przemek and Luca worked on this project while visiting CNetS in 2011 and collaborating with the Truthy team. Bravo!
[UPDATE: this position has been filled.]
The Center for Complex Networks and Systems Research has an open postdoctoral position to study how ideas propagate through complex online social networks. The position is funded by a McDonnell Foundation’s grant in Complex Systems. The appointment starts as early as possible after January 2013 for one year and is renewable for up to 2 additional years. The salary is competitive and benefits are generous.
The postdoc will join a dynamic and interdisciplinary team that includes computer, physical, and cognitive scientists. The postdoc will work with PIs Filippo Menczer and Alessandro Flammini, other postdocs, and several PhD students on analysis and modeling of social media data. Areas of focus will include information diffusion patterns, epidemic models for the spread of ideas, interactions between network traffic and structure dynamics, and agent-based models to explain the emergence of viral bursts of attention. Domains of study will include politics, scientific knowledge, and world events. Go to the grant page or project page for further details on the team and project.
The ideal candidate will have a PhD in computing or physical sciences; a strong background in analysis and modeling of complex systems and networks; and solid programming skills necessary to handle big data and develop large scale simulations.
To apply, email/send a CV and names and emails of three references to Tara Holbrook. Applications received by 15 December 2012 will receive full consideration, but applications will be considered until the position is filled.
Indiana University is an Equal Opportunity/Affirmative Action employer. Applications from women and minorities are strongly encouraged. IU Bloomington is vitally interested in the needs of Dual Career couples.
I was honored to give a keynote presentation at PLEAD 2012, the CIKM Workshop on Politics, Elections and Data. My talk was titled The diffusion of political memes in social media. The workshop was held in beautiful Maui Hawaii, but alas, I could not attend in person and gave the presentation remotely via skype 🙁
University and industry scientists are determining how to forecast significant societal events, ranging from violent protests to nationwide credit-rate crashes, by analyzing the billions of pieces of information in the ocean of public communications, such as tweets, web queries, oil prices, and daily stock market activity.
“We are automating the generation of alerts, so that intelligence analysts can focus on interpreting the discoveries rather than on the mechanics of integrating information,” said Naren Ramakrishnan, the Thomas L. Phillips Professor of Engineering in the computer science department at Virginia Tech. He is leading the team of computer scientists and subject-matter experts from Virginia Tech, the University of Maryland, Cornell University, Children’s Hospital of Boston, San Diego State University, University of California at San Diego, and Indiana University, and from the companies, CACI International Inc., and Basis Technology.
CNetS Professors Bollen and Rocha from the School of Informatics and Computing at Indiana University are members of this project. Prof. Bollen, has devised a way to evaluate the tone of tweets – calm, alert, vital, etc. — to predict stock market trends. Prof. Rocha, has developed bio-inspired methods to predict associations in biochemical, social, and knowledge networks, including web and e-mail systems.
Additional details: Researchers study new ways to forecast critical societal events.
Prof. Flammini (PI) and Menczer have been awarded a three-year, $2M grant from DARPA in the context of the Social Media in Strategic Communication (SMISC) program, whose primary goal is “to develop a new science of social networks built on an emerging technology base,” Our IU unit leads a three-group team that includes collaborators at Lockheed-Martin Advanced Technology Lab and the University of Michigan. The funded project is aimed at designing and implementing a system to detect online persuasion campaigns.