Transcription of Online Human-Bot Interactions: Detection, Estimation, and ...
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Online Human-Bot Interactions: Detection, Estimation, and ...
Online Human-Bot Interactions: Detection, Estimation, and CharacterizationOnur Varol,1,*Emilio Ferrara,2 Clayton A. Davis,1 Filippo Menczer,1 Alessandro Flammini11 Center for Complex Networks and Systems Research, indiana university , Bloomington, US2 Information Sciences Institute, university of southern California, Marina del Rey, CA, USAbstractIncreasing evidence suggests that a growing amount of socialmedia content is generated by autonomous entities knownas social bots. In this work we present a framework to de-tect such entities on Twitter. We leverage more than a thou-sand features extracted from public data and meta-data aboutusers: friends, tweet content and sentiment, network patterns,and activity time series. We benchmark the classificationframework by using a publicly available dataset of Twitterbots. This training data is enriched by a manually annotatedcollection of active Twitter users that include both humansand bots of varying sophistication.
1Center for Complex Networks and Systems Research, Indiana University, Bloomington, US ... University of Southern California, Marina del Rey, CA, US Abstract Increasing evidence suggests that a growing amount of social ... study how POS tags are distributed.
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