Skip to main content
Article thumbnail
Location of Repository

The Utility of Social and Topical Factors in Anticipating Repliers in Twitter Conversations

By Johannes Schantl, Claudia Wagner, Rene Kaiser and Markus Strohmaier

Abstract

Anticipating repliers in online conversations is a fundamental challenge for computer mediated communication systems which aim to make textual, audio and/or video communication as natural as face to face communication. The massive amounts of data that social media generates has facilitated the study of online conversations on a scale unimaginable a few years ago. In this work we use data from Twitter to explore the predictability of repliers, and investigate the factors which influence who will reply to a message. Our results suggest that social factors, which describe the strength of relations between users, are more useful than topical factors. This indicates that Twitter users ’ reply behavior is more impacted by social relations than by topics. Finally, we show that a binary classification model, which differentiates between users who will and users who will not reply to a certain message, may achieve an F1-score of 0.74 when using social features. Author Keywords Twitter, social media communication, reply behavior, reply predictio

Year: 2013
OAI identifier: oai:CiteSeerX.psu:10.1.1.353.5126
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://markusstrohmaier.info/d... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.