Astroturfers, Twitter-bombers and smear campaigners need beware this election season as a group of leading Indiana University information and computer scientists today unleashed Truthy.indiana.edu, a sophisticated new Twitter-based research tool that combines data mining, social network analysis and crowdsourcing to uncover deceptive tactics and misinformation leading up to the Nov. 2 elections. Combing through thousands of tweets per hour in search of political keywords, the team based out of IU’s School of Informatics and Computing will isolate patterns of interest and then insert those memes (ideas or patterns passed by imitation) into Twitter’s application programming interface (API) to obtain more information about the meme’s history.

In the run-up to the mid-term elections, Truthy uncovered a number of abuses such as robot-driven traffic to politician websites and networks of bot accounts controlled by individuals to promote fake news. These findings have been widely covered in the press, with mentions in The Atlantic, MIT Technology Review, PC World, New Scientist, NPR, Ars Technica, Fast Company, The Chronicle of Higher Education, The New York Times Magazine, and many other media. Read more here and here.

The focus of this research project is understanding how information propagates through complex socio-technical information networks. Leveraging large-scale behavioral trace data from online social networking platforms we are able to analyze and model the spread of information, from political discourse to market trends, in unprecedented detail.

Our work to date includes a number of core research themes. Truthy is a web-based system to analyze and visualize the diffusion of information on Twitter. The Truthy system evaluates thousands of tweets an hour to identify new and emerging bursts of activity around memes of various flavors. Building on this foundation we have undertaken several analyses of political communication on Twitter, addressing political polarization and cross-ideological communication, the automated prediction of political affiliation from network and text data, and partisan asymmetries in online political engagement. Members of the Truthy team have successfully applied a custom psycholinguistic sentiment analysis framework to the problem of forecasting key market indicators, technology which now underpins the trading decisions of a $40 million investment fund.

The current focus of the project follows three directions:

1. Expanding the platform to make the data more easily accessible and thus more useful to social scientists, reporters, and the general public.
2. Modeling efforts to better understand how information spreads, why some memes go viral, the role of sentiment on the diffusion process, the mutual interaction between traffic on the network and the emergent structure of the network.
3. Adopting network analysis methods in a machine learning framework to automatically detect astroturf in political campaigns.

Truthy in the Press

People

Principle Investigators

Fil Menczer

Sandro Flammini

Alex Vespignani

Johan Bollen

Research Team

Emilio Ferrara

Huina Mao

Lilian Weng

Karissa McKelvey

Qian Zhang

Clayton Davis

Azadeh Nematzadeh

Alumni

Michael Conover

Ruby Wang

Alex Rudnick

Jiayi Zhu

Jacob Ratkiewicz

Bruno Gonçalves

Mark Meiss

Przemyslaw Grabowicz

Snehal Patil

Luca Aiello

Papers

J DiGrazia, K McKelvey, J Bollen, and F Rojas
More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior. Under review, 2013.

Lilian Weng, Jacob Ratkiewicz, Nicola Perra, Bruno Goncalves, Carlos Castillo, Francesco Bonchi, Rossano Schifanella, Filippo Menczer, and Alessandro Flammini.
The role of information diffusion in the evolution of social networks. Proc. 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining KDD, 2013.
URL

Emilio Ferrara, Mohsen JafariAsbagh, Onur Varol, Vahed Qazvinian, Filippo Menczer, and Alessandro Flammini.
Clustering Memes in Social Media. Proc. IEEE/ACM Intl. Conf. on Advances in Social Networks Analysis and Mining ASONAM, 2013.

Q Zhang, N Perra, B Gonçalves, F Ciulla, and A Vespignani.
Characterizing scientific production and consumption in Physics. Nature Sci. Rep., (3) 1640, 2013.
URL

M Conover, E Ferrara, F Menczer, and A Flammini.
The Digital Evolution of Occupy Wall Street. PLoS ONE, (8)5:e64679, 2013.
URL

D Mocanu, A Baronchelli, N Perra, B Gonçalves, Q Zhang, et al.
The Twitter of Babel: Mapping World Languages through Microblogging Platforms. PLoS ONE, (8)4: e61981, 2013.
URL

McKelvey, K. Menczer, F.
Interoperability of Social Media Observatories. Web Science 2013, Web Observatory Workshop, May 5 2013.
URL

McKelvey, K. Menczer, F.
Design and Prototyping of a Social Media Observatory. WWW 2013, Web Observatory Workshop, May 17 2013.
URL

Conover MD, Davis C, Ferrara E, McKelvey K, Menczer F, Flammini A.
The Geospatial Characteristics of a Social Movement Communication Network. PLoS ONE 8(3): e55957, 2013.
URL

K. McKelvey, F. Menczer.
Truthy: Enabling the Study of Online Social Networks. CSCW 2013 Demonstration, 25 February 2013.
URL

M. Conover, B. Goncalves, A. Flammini, and F. Menczer.
Partisan Asymmetries in Online Political Activity. EPJ Data Science (1)6 18 June 2012.
URL

L. Weng, A. Flammini, A. Vespignani, and F. Menczer.
Competition among memes in a world with limited attention. Nature Sci. Rep., (2) 335, 2012.
URL

A. Vespignani.
Modeling Dynamical Processes in Complex Socio-technical Systems. Nature Physics, 8, 32-39, 2012.
URL

Karissa McKelvey, Alex Rudnick, Michael Conover, and Filippo Menczer.
Visualizing Communication on Social Media: Making Big Data Accessible. Proc. CSCW Workshop on Collective Intelligence as Community Discourse and Action, 2012.
URL

Jacob Ratkiewicz, Michael Conover, Mark Meiss, Bruno Goncalves, Alessandro Flammini, and Filippo Menczer.
Detecting and Tracking Political Abuse in Social Media. Proc. 5th International AAAI Conference on Weblogs and Social Media ICWSM, 2011.
URL

Michael Conover, Jacob Ratkiewicz, Matthew Francisco, Bruno Goncalves, Alessandro Flammini, and Filippo Menczer.
Political Polarization on Twitter. Proc. 5th International AAAI Conference on Weblogs and Social Media ICWSM, 2011.
URL

Conover, B Goncalves, J Ratkiewicz, A Flammini, and F Menczer.
Predicting the Political Alignment of Twitter Users. Proceedings of 3rd IEEE Conference on Social Computing SocialCom, 2011.
URL

M. Conover, J. Ratkiewicz, B. Goncalves, M. Francisco, A. Flammini, and F. Menczer.
Networks of Political Communication I: Multi-Mode Interactions in an Online Social Network. International School and Conference on Network Science NetSci, 2011.

Jacob Ratkiewicz, Michael Conover, Mark Meiss, Bruno Gonçalves, Snehal Patil, Alessandro Flammini, and Filippo Menczer.
Truthy: Mapping the Spread of Astroturf in Microblog Streams. Proc. 20th Intl. World Wide Web Conf. Companion WWW, 2011.
URL

B. Goncalves, M. Conover, A. Flammini, and F. Menczer.
Networks of Political Communication II: Partisan Engagement and Social Media. International School and Conference on Network Science NetSci, 2011.

B. Goncalves, M. Conover, and F. Menczer.
Abuse of social media and political manipulation. In Markus Jakobsson (Eds.), The Death of The Internet, Wiley, 2012.

L. Weng, A. Flammini, and F. Menczer.
An Information Propagation Model Based on User Interests. In H. Sayama, A. Minai, D. Braha, and Y. Bar-Yam (Eds.), Unifying Themes in Complex Systems Volume VIII: Proc. 8th International Conference on Complex Systems ICCS, 2011.

Datasets

• ICWSM 2011 Dataset: Truthy/Legitimate Classification
• ICWSM 2011 Dataset: Political Polarization on Twitter

Videos

• The Truthy Project Ferrets Out Online Deception - by WSJ
• Political Polarization on Twitter – presentation at ICWSM 2011
• Political Communication on Twitter: Misinformation, Polarization and Partisan Engagement - D2I seminar

Support

We gratefully acknowledge support from the Lilly Foundation (Data to Insight Center Research Grant), the National Science Foundation (ICES award CCF-1101743 on Meme Diffusion Through Mass Social Media), and the James S. McDonnell Foundation (complex systems grant on contagion of ideas in online social networks). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the funding agencies.

The interplay of human mobility patterns like those between local metropolitan commuters and long-range airline travelers during a global epidemic can be modeled in such detail so as to offer refined views of epidemics that could aid in public health emergency decision making, according to new research published by Professor Alessandro Vespignani’s research team at Indiana University. The findings, published this week in the Proceedings of the National Academy of Sciences‘ Online Early Edition, also note that with these refined computational strategies, new levels of accuracy about the behavior of targeted mobility networks and epidemic progression can be imagined. Contributing with Vespignani on the paper were research scientists Duygu Balcan and Bruno Goncalves of the IU School of Informatics and Computing, and the Pervasive Technology Institute, IU Physics Department graduate student Hao Hu and research scientists Vittoria Colizza and Jose Ramasco of the Institute for Scientific Interchange Foundation in Torino, Italy.  More…

Much as meteorologists predict the path and intensity of hurricanes, CNetS’ Alessandro Vespignani believes we will one day predict with unprecedented foresight, specificity and scale such things as the economic and social effects of billions of new Internet users in China and India, or the exact location and number of airline flights to cancel around the world in order to halt the spread of a pandemic. In the July 24 “Perspectives” section of the journal Science, Vespignani writes that advances in complex networks theory and modeling, along with access to new data, will enable humans to achieve true predictive power in areas never before imagined. This capability will be realized as the one wild card in the mix — the social behavior of large aggregates of humans — becomes more definable through progress in data gathering, new informatics tools and increases in computational power. More…

It’s a terrifying word. But what does it really mean? The outbreak of H1N1 is the latest deadly global battle between man and virus. As we learn more about how viruses mutate, an international effort is underway to vanquish humanity’s most lethal foes. CNetS’ Alessandro Vespignani to appear on Science Channel program about the “global battle between man and virus”.

GLEaM is a Global Epidemic and Mobility modeler that integrates sociodemographic and population mobility data in spatially structured stochastic disease models to simulate the spread of epidemics at the worldwide scale. The GLEaM team and its PI, Alex Vespignani, have been featured in many news reports about projections of the spread of H1N1 (Mexican flu). Read more about GLEaM…

Complex Networks Collaboratory

Cx-Nets  is a virtual collaboratory of three research groups that despite their far apart geographical locations pursue the same research agenda in close collaboration. Active research areas include:

• Network theory, structure and models
• Information Networks
• Epidemic modeling
• Social systems
• Infrastructures
• Biological networks

The Cx-Nets website is also intended as an information exchange point with links to conferences, tools and references useful for the network science community.

Alex Vespignani (PI)

Sandro Flammini

Fil Menczer

Research and Creativity Activity profiles research by CNetS faculty Filippo Menczer and Alessandro Vespignani and their groups in a special issue on networks. More…

Alex Vespignani

CNetS Professor Alex Vespignani has been elected to fellowship in the American Physical Society, the preeminent organization of physicists in the United States. Vespignani was honored for his contribution to the statistical physics of complex networks, in particular his seminal work on the spreading of viruses in real networks. More…

The National Institutes of Health has given $1.2 million to Indiana University researchers to build the ultimate international epidemic research tool. Principle investigators Katy Börner, Steven J. Sherman and Alessandro Vespignani will oversee the project, EpiC, which they hope will make the sharing and re-using of epidemics datasets and algorithms as easy as sharing videos via YouTube. The three researchers come from three distinct areas of the campus — the School of Library and Information Science, the Department of Psychological and Brain Sciences in the College of Arts and Sciences, and the School of Informatics, respectively. Additional members of the evolving team are IU researchers Duygu Balcan, Weixia Huang and Bruce W. Herr. Read the full press release or more info and figures….