The CNetS poster “The Rise of Social Bots in Online Social Networks” by Emilio Ferrara, Onur Varol, Prashant Shiralkar, Clayton Davis, Filippo Menczer, and Alessandro Flammini won a Best Poster Award at CCS 2015. The poster was presented by Clayton Davis. The results will also appear in the paper “The Rise of Social Bots” to be published in Comm. ACM (in press, preprint).
The paper “Modularity and the Spread of Perturbations in Complex Dynamical Systems” by Artemy Kolchinsky, Alexander J. Gates and Luis M. Rocha, and the poster “Information Theoretic Structures of the French Revolution” by Alexander Barron, Simon DeDeo and Rebecca Spang won additional awards.
Finally, our former postdoctoral scientist Bruno Gonçalves (now tenured faculty member at Aix-Marseille Université) received a Junior Scientist Award from the Complex Systems Society for his contributions to the study of human social behavior from large-scale online attention and behavioral data. This is the second Junior Scientist Award for CNetS (the first was won by Filippo Radicchi).
Congratulations to the CNetS team!
Predicting popularity and success in cultural markets is hard due to strong inequalities and inherent unpredictability. A good example comes from the world of fashion, where industry professionals face every season the difficult challenge of guessing who will be the next seasons’ top models. A recent study by CNetS graduate student Jaehyuk Park, research scientist Giovanni Luca Ciampaglia (also at the IU Network Science Institute), and research scientist Emilio Ferrara (now at the University of Southern California) is now showing that early success in modeling can be predicted from the digital traces left by the buzz on social media such as Instagram. The study has been accepted for presentation at the 19th ACM conference on Computer-Supported Cooperative Work and Social Computing (CSCW’16). The work has been covered in the media by the MIT Technology Review, Die Welt, Fusion, and iTNews.
Big success for CNetS researchers at the Conference on Complex Systems (CCS’15)! Here are the accepted talks from our center:
- Computational fact checking from knowledge networks by Giovanni Luca Ciampaglia, Prashant Shiralkar, Johan Bollen, Luis M Rocha, Filippo Menczer and Alessandro Flammini
- Control of complex networks requires structure and dynamics by Alexander Gates and Luis M. Rocha
- Darwin’s Semantic Voyage by Jaimie Murdock, Simon DeDeo, and Colin Allen
- Defining and Identifying Sleeping Beauties in Science by Qing Ke, Emilio Ferrara, Filippo Radicchi and Alessandro Flammini
- Detecting conflict in social unrest using Instagram* by Rion Brattig Correia, Kwan Nok Chan and Luis M. Rocha
- Detecting Campaigns in Social Media by Onur Varol, Emilio Ferrara, Filippo Menczer and Alessandro Flammini
- Discourse Polarization in the US Congress by Rion Brattig Correia, Kwan Nok Chan and Luis M. Rocha
- Eigenmood Twitter Analysis: measuring collective mood variation by Ian B. Wood, Joana Gonçalves-Sá, Johan Bollen and Luis M. Rocha
- Evolution of Online User Behavior During a Social Upheaval by Onur Varol, Emilio Ferrara, Christine Ogan, Filippo Menczer and Alessandro Flammini
- How human perception of the urban environment influences the abandonment process by Stefani Crabstree, Simon DeDeo
- Information theoretic structures of the French Revolution by Alexander Barron, Simon DeDeo, and Rebecca Spang
- Measuring Emotional Contagion in Online Social Networks by Zeyao Yang, Emilio Ferrara
- Modularity and the Spread of Perturbations in Complex Dynamical Systems* by Artemy Kolchinsky, Alexander J. Gates and Luis M. Rocha
- On Predictability of Rare Events Leveraging Social Media by Lei Le, Emilio Ferrara and Alessandro Flammini
- Optimal network modularity for information diffusion by Azadeh Nematzadeh, Emilio Ferrara, Alessandro Flammini and Yong-Yeol Ahn
- Redundancy and control in complex networks by Luis M. Rocha
- The Rise of Social Bots in Online Social Networks by Emilio Ferrara, Onur Varol, Prashant Shiralkar, Clayton Davis, Filippo Menczer and Alessandro Flammini
Simon DeDeo will also deliver one of the plenary talks. *Denotes papers “starred”, or designated as especially worthwhile by the CCS15 program committee.
Why do some research papers remain dormant for years and then suddenly explode with great impact upon the scientific community? These “sleeping beauties” are the subject of a new study by CNetS researchers Qing Ke, Emilio Ferrara, Filippo Radicchi, and Alessandro Flammini published in the Proceedings of the National Academy of Sciences. The study provides empirical evidence that a paper can truly be ahead of its time. A ‘premature’ topic may fail to attract attention even when it is introduced by authors who have already established a strong scientific reputation. The authors show that sleeping beauties can be dormant for many decades, and are more common than previously thought. The findings have been covered by media such as Nature and The New York Times. More…
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, 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.
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.
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 misleading information echoed in an 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.
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
Congratulations to Onur Varol, Emilio Ferrara, Chris Ogan, Fil Menczer, and Sandro Flammini for winning the ACM Web Science 2014 Best Paper Award with their paper Evolution of online user behavior during a social upheaval (preprint). In the paper, the authors study the pivotal role played by Twitter during the political mobilization of the Gezi Park movement in Turkey. By analyzing over 2.3 million tweets produced during 25 days of protest in 2013, the authors show that similarity in trends of discussion mirrors geographic cues. The analysis also reveals that the conversation becomes more democratic as events unfold, with a redistribution of influence over time in the user population. Finally, the study highlights how real-world events, such as political speeches and police actions, affect social media conversations and trigger changes in individual behavior.
Congratulations also go to Luca Aiello and Rossano Schifanella, both former visitors and members of CNetS, who won the Best Presentation Award with their talk on Reading the Source Code of Social Ties (preprint).
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!
On August 11, 2013, the New York Times published an article by Ian Urbina with the headline: I Flirt and Tweet. Follow Me at #Socialbot. The article reports on how socialbots (software simulating people on social media) are being designed to sway elections, to influence the stock market, even to flirt with people and one another. Fil Menczer is quoted: “Bots are getting smarter and easier to create, and people are more susceptible to being fooled by them because we’re more inundated with information.” The article also mentions the Truthy project and some of our 2010 findings on political astroturf.
Inspired by this, the writers of The Good Wife consulted with us on an episode in which the main character finds that a social news site is using a socialbot to bring traffic to the site, defaming her client. The episode aired on November 24, 2013, on CBS (Season 5 Episode 9, “Whack-a-Mole”). Good show!
A story in Nature discusses a recent paper (preprint) from CNetS members Jasleen Kaur, Filippo Radicchi and Fil Menczer on the universality of scholarly impact metrics. In the paper, we present a method to quantify the disciplinary bias of any scholarly impact metric. We use the method to evaluate a number of established scholarly impact metrics. We also introduce a simple universal metric that allows to compare the impact of scholars across scientific disciplines. Mohsen JafariAsbagh integrated this metric into Scholarometer, a crowdsourcing system developed by our group to collect and share scholarly impact data. The Nature story highlight how one can use normalized impact metrics to rank all scholars, as illustrated in the widget shown here.