• Title/Summary/Keyword: detection of incivility

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Detection of Incivility based on Attention-embedding and multi-channel CNN (어텐션임베딩과 다채널 CNN 기반 반시민성 검출 알고리즘)

  • Park, Youn-Jung;Lee, Se-Young;Keum, Hee-Jo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.12
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    • pp.1880-1889
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    • 2022
  • 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.