News Big Data Analysis on Cyber Violence Before and After the Outbreak of COVID-19*

Abstract

This study analyzes social agendas and changes in perception of cyber violence before and after the outbreak of COVID-19 using news big data. To this end, LDA topic modeling analysis technique was conducted. As a result of the analysis, first, as keywords such as ‘school, student, education, damage, investigation, prevention’ appeared as high-ranking keywords in both periods, it was confirmed that the main target of social interest in cyber violence was in students and school sites. Second, the number of news articles related to cyber violence was about twice as high as in the previous period, and new topics such as fair punishment for cyber violence, its system improvement and legislation, and strengthening digital media communication with the public emerged. Third, as a result of reclassifying all the derived topics into three major categories, the topic dealing with the harmful effects of cyber violence was the most at 43.3%, its prevention and education 30.8%, and cyber violence system and legislation 26.0%. appeared in sequence. Based on these analysis results, implications for the participation and role of all members of society in cyber violence were presented, and limitations of the study and suggestions for follow-up studies were made.