A Trolling Hierarchy in Social Media and A Conditional Random Field For Trolling Detection

TL;DR

This paper introduces a hierarchical model for detecting trolling in social media, categorizes trolling behaviors, and provides a new annotated dataset to facilitate research in trolling detection.

Contribution

It proposes a novel model that jointly predicts trolling intention, interpretation, disclosure, and response, along with a new dataset for trolling analysis.

Findings

A comprehensive trolling categorization based on politeness research.

A joint prediction model for multiple trolling aspects.

A new annotated dataset of social media conversations involving trolls.

Abstract

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.