텍스트 마이닝을 통한 메타버스 아바타 성착취 처벌에 대한 대중의 인식 분석

초록

With the development of virtual reality technology and the release of devices offering more lifelike experiences, it’s essential to discuss newly emerging avatar sexual abuse crimes. This study intends to contribute to the discussion on countermeasures against avatar sexual abuse crimes by grasping the public’s opinions regarding the punishment of users who engage in sexual activity against other avatars. In this study, 13 YouTube channel videos about avatar sexual abuse were selected and 1,321 user comments were analyzed using text mining analysis techniques. Python 3.9 development tools were used for frequency analysis and LDA topic modeling on 10,201 words extracted from the user comments. Five topics of user comments were identified: ‘Game Situation-Skeptic’, ‘Game Situation–User’s Own Countermeasure’, ‘External Regulation’, ‘Simple Criticism’, and ‘Avatar Personalization’. Most comments tended to be skeptical or critical of the videos advocating legal punishment of avatar sexual abusers. In addition, many users equated avatar sexual abuse in the virtual world with situations in general video games and suggested regulation of platform operators or users’ own countermeasure against the crime rather than introducing legal punishment. Based on these results, more discussions are needed to draw social consensus on the necessity and legitimacy of legal punishment for avatar sexual abuse offenders.

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