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http://dx.doi.org/10.6109/jkiice.2022.26.12.1880

Detection of Incivility based on Attention-embedding and multi-channel CNN  

Park, Youn-Jung (Global Convergence Contents Research Center, Sungkyunkwan University)
Lee, Se-Young (Department of media communication, Sungkyunkwan University)
Keum, Hee-Jo (Department of media communication, Sungkyunkwan University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.26, no.12, 2022 , pp. 1880-1889 More about this Journal
Abstract
The online portal platform provides online news with online comments, but the anonymity of comments causes incivility, and online comments are considered social problems. While there are many foreign language-based incivility detection studies, in-depth research is not being conducted in Korea since there has not been implemented Korean language dataset which is labeled detailed criteria of incivility. In this study, the incivility notation of comments was conducted in a total of 13 items, uncivil words were summarized. Furthermore, Attention algorithm was applied to each comment and summary to extract embedding vectors. 2-d CNN followed at the end to detect incivility in given data. As a result, we showed that the proposed algorithm is useful for anti-citizen detection such as name-calling and offensive tones. This study is expected to contribute to the formation of a healthy online comment culture by detecting uncivil comments which hinder democratic discourse.
Keywords
Online commnets; detection of incivility; Attention Algorithm; CNN;
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