About the Observatory on Social Media

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

One goal of this project is to study how social network structure, finite attention, popular sentiment, user influence, and other factors affect the manner in which information is disseminated. A second goal is to better understand how social media can be abused, for example by malicious social bots, astroturf, orchestrated campaigns, and online hoaxes.

Our work to date includes a number of core research themes:

  1. Theoretical models and empirical analyses to better understand how information spreads, how the structure of social networks can help predict which memes are likely to become viral, the role of limited attention and sentiment on the diffusion process, and the mutual interaction between traffic on the network and the emergent structure of the network.
  2. Computational social science methods exploring the correlations between online and offline events. Examples of research to date include analyses of geographic and temporal patterns in movements like Occupy Wall Street, societal unrest in Turkey, polarization and cross-ideological communication in online discourse, partisan asymmetries in political engagement, the use of social media data to predict election outcomes and forecast key market indicators, and the geographic diffusion of trending topics.
  3. Development of an Observatory to share and explore data derived from our meme diffusion analytics, making this data more easily accessible and thus more useful to social scientists, reporters, and the general public. Deployment of machine learning algorithms to help classify content and its producers. Applications include social bot detection, an API for exploring historical Twitter data, and visualizations of temporal, geographic, and network patterns.

Support

NSF logo JSMF logo

We gratefully acknowledge support from National Science Foundation award CCF-1101743 (ICES proposal on Meme Diffusion Through Mass Social Media) and James S. McDonnell Foundation complex systems grant on Contagion of Ideas in Online Social Networks, as well as a seed Data to Insight grant from the Lilly Endowment. 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.

Team

Filippo Menczer and Alessandro Flammini coordinate this research project at Indiana University and are the Principal Investigators on the NSF, JSMF, and Lilly grants.

The project contributed to the support and training of postdoctoral fellows Diego Fregolente, Ruby Wang, and Giovanni Luca Ciampaglia; and of many graduate students who were involved in various aspects of the research: Clayton A Davis, Karissa McKelvey, Mark Meiss, Jacob Ratkiewicz, Michael Conover, Lilian Weng, Qian Zhang, Huina Mao, Onur Varol, Azadeh Nematzadeh, Pablo Moriano, Alex Rudnick, Jiayi Zhu, Rachael Filper, Jasleen Kaur, Prashant Shiralkar, Xiaoming Gao, Andrew Younge, Tak-Lon Wu, Pik-Mai Hui, and Zeyao Yang, as well as undergraduate students Bryce Lewis, Kehontas Rowe, Keychul Chung, and Alex Hong.

We acknowledge the collaboration of many researchers. Alessandro Vespignani and Johan Bollen were Co-PIs on the NSF grant. Several other key collaborators at IU and other institutions contributed to various research thrusts of this project: Emilio Ferrara, Bruno Gonçalves, Przemyslaw Grabowicz, Luca Aiello, and Judy Qiu. Other collaborators include Nicola Perra, Marton Karsai, Fabio Rojas, Joseph DiGrazia, Chato Castillo, Francesco Bonchi, Rossano Schifanella, Snehal Patil, Emily Metzgar, Luis Rocha, YY Ahn, Geoffrey Fox, and Chris Ogan.

Finally we wish to acknowledge the support of the technical staff of the IU Network Science Instutute: Valentin Pentchev, Scott McCaulay, Chathuri Peli Kankanamalage, and Ben Serrette.