Self-disclosure topic model for Twitter conversations JinYeong Bak Chin-Yew Lin Alice Oh Department of Computer Science Microsoft Research Asia Department of Computer Science KAIST Beijing 100080, P.R. China KAIST Daejeon, South Korea
[email protected] Daejeon, South Korea
[email protected] [email protected] Abstract is social support from others (Wills, 1985; Der- lega et al., 1993), shown also in online social net- Self-disclosure, the act of revealing one- works (OSN) such as Twitter (Kim et al., 2012). self to others, is an important social be- Receiving social support would then lead the user havior that contributes positively to inti- to be more active on OSN (Steinfield et al., 2008; macy and social support from others. It Trepte and Reinecke, 2013). In this paper, we seek is a natural behavior, and social scien- to understand this important social behavior using tists have carried out numerous quantita- a large-scale Twitter conversation data, automati- tive analyses of it through manual tagging cally classifying the level of self-disclosure using and survey questionnaires. Recently, the machine learning and correlating the patterns with flood of data from online social networks subsequent OSN usage. (OSN) offers a practical way to observe Twitter conversation data, explained in more de- and analyze self-disclosure behavior at an tail in section 4.1, enable a significantly larger unprecedented scale. The challenge with scale study of naturally-occurring self-disclosure such analysis is that OSN data come with behavior, compared to traditional social science no annotations, and it would be impos- studies.