Detecting comments on news articles in microblogs

Alok Kothari, Walid Magdy, Kareem Darwish, Ahmed Mourad, Ahmed Taei

Research output: Contribution to conferencePaper

Abstract

A reader of a news article would often be interested in the comments of other readers on anarticle, because comments give insight into popular opinions or feelings toward a given piece of news. In recent years, social media platforms, such as Twitter, have become a social hub for users to communicate and express their thoughts. This includes sharing news articles and commenting on them. In this paper, we propose an approach for identifying "comment-tweets" that comment on news articles. We discuss the nature of comment-tweets and compare them to subjective tweets. We utilize a machine learning-based classification approach for distinguishing between comment-tweets and others that only report the news. Our approach is evaluated on the TREC-2011 Microblog track data after applying additional annotations to tweets containing comments. Results show the effectiveness of our classification approach. Furthermore, we demonstrate the effectiveness of our approach on live news articles.

Original languageEnglish
Pages293-302
Number of pages10
Publication statusPublished - 1 Jan 2013
Event7th International AAAI Conference on Weblogs and Social Media, ICWSM 2013 - Cambridge, MA, United States
Duration: 8 Jul 201311 Jul 2013

Other

Other7th International AAAI Conference on Weblogs and Social Media, ICWSM 2013
CountryUnited States
CityCambridge, MA
Period8/7/1311/7/13

    Fingerprint

ASJC Scopus subject areas

  • Media Technology

Cite this

Kothari, A., Magdy, W., Darwish, K., Mourad, A., & Taei, A. (2013). Detecting comments on news articles in microblogs. 293-302. Paper presented at 7th International AAAI Conference on Weblogs and Social Media, ICWSM 2013, Cambridge, MA, United States.