Tag Archives: detection

DESPIC team presents Bot Or Not demo and six posters at DoD meeting

IU Bot or Bot poster 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 ObservatoryMeme Clustering in  Streaming DataPersuasion Detection in Social StreamsHigh-Resolution Anomaly Detection in Social Streams, and Early Detection and Analysis of Rumors. See more coverage of BotOrNot on PCWorld, IDS, BBCPolitico, and MIT Technology Review.