About Truthy

Research Objectives

Truthy is a 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. The data and statistics provided by Truthy are designed to aid in the study of social epidemics: How do memes propagate through the Twittersphere? What causes a burst of popularity?

We also plan to use Truthy to detect political smears, astroturfing, misinformation, and other social pollution. While the vast majority of memes arise in a perfectly organic manner, driven by the complex mechanisms of life on the Web, some are engineered by the shady machinery of high-profile congressional campaigns. Truthy uses a sophisticated combination of text and data mining, social network analysis, and complex networks models.

System Architecture

System Architecture diagram

Streaming Twitter data is acquired in real-time from a sample of public tweets. We extract all memes, defined to be @mentions, #hash_tags, and URLs. Further, we isolate memes of interest by considering only those memes that have just undergone significant changes in volume, or those that account for a significant portion of the total volume. We insert these memes in the database, and use the Twitter API to get more information on each meme and apply our analytics and visualization algorithms to provide a deeper view of how these memes spread.

Research Papers and Support

Please visit the project page for details on publications. Truthy is based in part upon work supported by the National Science Foundation under Grant No. CCF-1101743 and the James S. McDonnell Foundation. 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.


Indiana University Center for Complex Networks & Systems Research