Academic Commons

Presentations (Communicative Events)

Detecting Influencers in Written Online Conversations

Biran, Or; Rosenthal, Sara; Andreas, Jacob; McKeown, Kathleen; Rambow, Owen

It has long been established that there is a correlation between the dialog behavior of a participant and how influential he or she is perceived to be by other discourse participants. In this paper we explore the characteristics of communication that make someone an opinion leader and develop a machine learning based approach for the automatic identification of discourse participants that are likely to be influencers in online communication. Our approach relies on identification of three types of conversational behavior: persuasion, agreement/disagreement, and dialog patterns.


  • thumnail for influencer_naacl_lsm_2012.pdf influencer_naacl_lsm_2012.pdf application/pdf 172 KB Download File

More About This Work

Academic Units
Computer Science
Published Here
April 24, 2013
Academic Commons provides global access to research and scholarship produced at Columbia University, Barnard College, Teachers College, Union Theological Seminary and Jewish Theological Seminary. Academic Commons is managed by the Columbia University Libraries.