• Journal of Internet Computing and Services
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• v.25 no.5
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• pp.163-169
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• 2024

This study aims to examine the influence of exposure to harmful content and digital hate speech on adolescents' exposure to digital sexual crimes, an issue that has been escalating in society. Additionally, it seeks to verify the mediating effect of digital hate speech in the relationship between exposure to harmful content and exposure to digital sexual crimes. To achieve this, the research model was investigated using structural equation modeling (SEM) with data from 9,218 adolescents who participated in the 2023 Cyberbullying Survey. The findings confirmed both the direct influence of harmful content exposure and digital hate speech on adolescents' exposure to digital sexual crimes, as well as the mediating effect of digital hate speech in the relationship between harmful content exposure and digital sexual crime exposure. Based on these research findings, the study proposed for preventing adolescents' exposure to digital sexual crimes.

• Informatization Policy
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• v.30 no.2
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• pp.3-21
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• 2023

The recent Internet environment demands a new approach to Internet content regulation. The need for regulation on the Internet has been recognized due to the rise of digital sex crimes, illegal information such as drugs and suicide, fake news, hate speech, false consumer reviews, and harmful content for young people. This article attempts to analyze the legislative, judicial, and administrative aspects of Internet content regulation in Korea. It covers the current status and characteristics of the Internet content regulation law, the judicial judgment on KCSC's communications deliberation and regulation, and the process and characteristics of KCSC's communications deliberation. Problems in Korea's communications deliberation system were addressed through legislative, judicial, and administrative approaches. This article concludes with policy suggestions for improving Internet content regulation in Korea.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1537-1542
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• 2017

Emotion plays a key role in both generating and understanding narrative. In this article we analyzed the emotions represented in a movie script based on 8 emotion types from the wheel of emotions by Plutchik. First we conducted manual emotion tagging scene by scene. The most dominant emotions by manual tagging were anger, fear, and surprise. It makes sense when the film script we analyzed is a thriller-genre. We assumed that the emotions around the climax of the story would be heightened as the tension grew up. From manual tagging we could identify three such duration when the tension is high. Next we analyzed the emotions in the same script using Python-based NLTK VADERSentiment tool. The result showed that the emotions of anger and fear were most matched. The emotion of surprise, anticipation, and disgust, however, scored lower matching.