The DARPA Twitter Bot Challenge

From politicians and nation states to terrorist groups, numerous organizations reportedly conduct explicit campaigns to influence opinions on social media, posing a risk to freedom of expression. Thus, there is a need to identify and eliminate "influence bots" - realistic, automated identities that illicitly shape discussions on sites like Twitter and Facebook - before they get too influential.

[1]  Thomas Elkjer Nissen.  Terror.com – IS’s Social Media Warfare in Syria and Iraq , 2014 .

[2]  Yoav Freund,et al.  A decision-theoretic generalization of on-line learning and an application to boosting , 1997, EuroCOLT.

[3]  Hans-Peter Kriegel,et al.  LOF: identifying density-based local outliers , 2000, SIGMOD '00.

[4]  Diego Reforgiato Recupero,et al.  OASYS: An Opinion Analysis System , 2006, AAAI 2006.

[5]  Robert F. Simmons,et al.  Natural language question-answering systems: 1969 , 1970, CACM.

[6]  Thomas S. Huang,et al.  Graph Regularized Nonnegative Matrix Factorization for Data Representation. , 2011, IEEE transactions on pattern analysis and machine intelligence.

[7]  V. S. Subrahmanian,et al.  Accurately detecting trolls in Slashdot Zoo via decluttering , 2014, 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014).

[8]  Leonard Bolc,et al.  Natural language question answering systems , 1980 .

[9]  Jaime G. Carbonell,et al.  Machine learning research , 1981, SGAR.

[10]  Rossano Schifanella,et al.  People Are Strange When You're a Stranger: Impact and Influence of Bots on Social Networks , 2012, ICWSM.

[11]  V. S. Subrahmanian,et al.  Using sentiment to detect bots on Twitter: Are humans more opinionated than bots? , 2014, 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014).

[12]  Kristina Lerman,et al.  Tripartite graph clustering for dynamic sentiment analysis on social media , 2014, SIGMOD Conference.

[13]  Sushil Jajodia,et al.  Detecting Automation of Twitter Accounts: Are You a Human, Bot, or Cyborg? , 2012, IEEE Transactions on Dependable and Secure Computing.

[14]  Hans-Peter Kriegel,et al.  Density-based clustering of uncertain data , 2005, KDD '05.

[15]  Yoav Freund,et al.  A decision-theoretic generalization of on-line learning and an application to boosting , 1995, EuroCOLT.

[16]  Brian D. Davison,et al.  Empirical study of topic modeling in Twitter , 2010, SOMA '10.

[17]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[18]  George Danezis,et al.  SybilInfer: Detecting Sybil Nodes using Social Networks , 2009, NDSS.

[19]  Kyumin Lee,et al.  Seven Months with the Devils: A Long-Term Study of Content Polluters on Twitter , 2011, ICWSM.

[20]  Aram Galstyan,et al.  Information transfer in social media , 2011, WWW.

[21]  Kristina Lerman,et al.  Entropy-based Classification of 'Retweeting' Activity on Twitter , 2011, ArXiv.

[22]  V. S. Subrahmanian,et al.  Using Twitter Sentiment to Forecast the 2013 Pakistani Election and the 2014 Indian Election , 2015, IEEE Intelligent Systems.

[23]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[24]  Joseph Weizenbaum,et al.  and Machine , 1977 .

[25]  Jacob Ratkiewicz,et al.  Truthy: mapping the spread of astroturf in microblog streams , 2010, WWW.

[26]  A. Kata.  Anti-vaccine activists, Web 2.0, and the postmodern paradigm--an overview of tactics and tropes used online by the anti-vaccination movement. , 2012, Vaccine.

[27]  Jean-Loup Guillaume,et al.  Fast unfolding of communities in large networks , 2008, 0803.0476.

[28]  Diego Reforgiato Recupero,et al.  AVA: Adjective-Verb-Adverb Combinations for Sentiment Analysis , 2008, IEEE Intelligent Systems.

[29]  Michael Kaminsky,et al.  SybilGuard: Defending Against Sybil Attacks via Social Networks , 2008, IEEE/ACM Transactions on Networking.

[30]  Joseph Weizenbaum,et al.  ELIZA—a computer program for the study of natural language communication between man and machine , 1966, CACM.

[31]  Jacob Ratkiewicz,et al.  Detecting and Tracking the Spread of Astroturf Memes in Microblog Streams , 2010, ArXiv.