Name
Title | ||
|---|---|---|
Dynamic user-level affect analysis in social media: Modeling violence in the Dark Web |
Abstract | ||
|---|---|---|
Affect represents a person's emotions toward objects, issues or other persons. Recent years have witnessed a surge in studies of users' affect in social media, as marketing literature has shown that users' affect influences decision making. The current literature in this area, however, has largely focused on the message level, using text-based features and various classification approaches. Such analyses not only overlook valuable information about the user who posts the messages, but also fail to consider that users' affect may change over time. To overcome these limitations, we propose a new research design for social media affect analysis by specifically incorporating users' characteristics and the time dimension. We illustrate our research design by applying it to a major Dark Web forum of international Jihadists. Empirical results show that our research design allows us to draw on theories from other disciplines, such as social psychology, to provide useful insights on the dynamic change of users' affect in social media. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ISI.2011.5984041 | ISI |
Keywords | Field | DocType |
social media,social network analysis,affect analysis,text-based features,pattern classification,persuasion,internet,time dimension,dark web,classification approaches,social networking (online),text analysis,dynamic user-level affect analysis,media,social psychology,psychology | Data mining,Research design,Social media,Persuasion,Computer security,Computer science,Social network analysis,Deep Web,Multiple time dimensions,The Internet | Conference |
ISBN | Citations | PageRank |
978-1-4577-0082-8 | 2 | 0.36 |
References | Authors | |
13 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shuo Zeng | 1 | 37 | 2.94 |
| Mingfeng Lin | 2 | 8 | 1.49 |
| Hsinchun Chen | 3 | 9569 | 813.33 |