TY - GEN
T1 - Identifying the social signals that drive online discussions
T2 - 26th International Conference on Computer Communications and Networks, ICCCN 2017
AU - Horne, Benjamin D.
AU - Adali, Sibel
AU - Sikdar, Sujoy
N1 - Publisher Copyright: © 2017 IEEE.
PY - 2017/9/14
Y1 - 2017/9/14
N2 - Increasingly people form opinions based on information they consume on online social media. As a result, it is crucial to understand what type of content attracts people's attention on social media and drive discussions. In this paper we focus on online discussions. Can we predict which comments and what content gets the highest attention in an online discussion? How does this content differ from community to community? To accomplish this, we undertake a unique study of Reddit involving a large sample comments from 11 popular subreddits with different properties. We introduce a large number of sentiment, relevance, content analysis features including some novel features customized to reddit. Through a comparative analysis of the chosen subreddits, we show that our models are correctly able to retrieve top replies under a post with great precision. In addition, we explain our findings with a detailed analysis of what distinguishes high scoring posts in different communities that differ along the dimensions of the specificity of topic and style, audience and level of moderation.
AB - Increasingly people form opinions based on information they consume on online social media. As a result, it is crucial to understand what type of content attracts people's attention on social media and drive discussions. In this paper we focus on online discussions. Can we predict which comments and what content gets the highest attention in an online discussion? How does this content differ from community to community? To accomplish this, we undertake a unique study of Reddit involving a large sample comments from 11 popular subreddits with different properties. We introduce a large number of sentiment, relevance, content analysis features including some novel features customized to reddit. Through a comparative analysis of the chosen subreddits, we show that our models are correctly able to retrieve top replies under a post with great precision. In addition, we explain our findings with a detailed analysis of what distinguishes high scoring posts in different communities that differ along the dimensions of the specificity of topic and style, audience and level of moderation.
UR - https://www.scopus.com/pages/publications/85032277746
U2 - 10.1109/ICCCN.2017.8038388
DO - 10.1109/ICCCN.2017.8038388
M3 - Conference contribution
T3 - 2017 26th International Conference on Computer Communications and Networks, ICCCN 2017
BT - 2017 26th International Conference on Computer Communications and Networks, ICCCN 2017
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 31 July 2017 through 3 August 2017
ER -