A Trolling Hierarchy in Social Media and A Conditional Random Field For Trolling Detection
Not on the map. Why?
Abstract (arXiv)
An-ever increasing number of social media websites, electronic newspapers and Internet forums allow visitors to leave comments for others to read and interact. This exchange is not free from participants with malicious intentions, which do not contribute with the written conversation. Among different communities users adopt strategies to handle such users. In this paper we present a comprehensive categorization of the trolling phenomena resource, inspired by politeness research and propose a model that jointly predicts four crucial aspects of trolling: intention, interpretation, intention disclosure and response strategy. Finally, we present a new annotated dataset containing excerpts of conversations involving trolls and the interactions with other users that we hope will be a useful resource for the research community.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 7 Apr 2017.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2023: 1.
1 paper.
- 2023Conversation Modeling to Predict Derailmentcited by 2
- 2023Conversation Modeling to Predict Derailment20 Mar 2023