Emotion -and area-driven topic shift analysis in social media discussions
Kamil Topal, Mehmet Koyutürk, Gültekin Özsoyoğlu · 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) · 2016
Internet-based social media platforms allow individuals to discuss/comment on the “topic” of an article in an interactive manner. The topic of a comment/reply in these discussions occasionally shifts, sometimes drastically and abruptly, other times slightly, away from the topic of the article. In this paper we study the phenomena of topic shifts in article-originated social media comments, and identify quantitatively the effects on topic shifts of comments (i) emotion levels (of various emotion dimensions), (ii) topic areas, and (iii) the structure of the discussion tree. We show that, with a better understanding of the topic shift phenomena in comments, automated systems can easily be built to personalize and cater to the comment-browsing and comment-viewing needs of different users.