Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
9-2019
Abstract
Despite the considerable interest in the detection of toxic comments, there has been little research investigating the causes -- i.e., triggers -- of toxicity. In this work, we first propose a formal definition of triggers of toxicity in online communities. We proceed to build an LSTM neural network model using textual features of comments, and then, based on a comprehensive review of previous literature, we incorporate topical and sentiment shift in interactions as features. Our model achieves an average accuracy of 82.5% of detecting toxicity triggers from diverse Reddit communities.
Keywords
Neural networks, Reddit, Social media, Toxicity, Trigger detection
Discipline
Theory and Algorithms
Research Areas
Data Science and Engineering
Publication
Proceedings of the 30th ACM Conference on Hypertext and Social Media, Germany, September 17-20
Editor
ALMEREKHI, Hind; KWAK, Haewoon; JANSEN, Bernard J.; SALMINEN, Joni
First Page
291
Last Page
292
ISBN
9781450368858
Identifier
10.1145/3342220.3344933
Publisher
Association for Computing Machinery, Inc
City or Country
New York
Citation
1
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi,org/10.1145/3342220.3344933