Anti-Asian bullying and harassment are prevalent since the coronavirus outbreak emerged (COVID-19). Not only do anti-Asian bullying and violence take place worldwide, but also bullying takes place among Asians. Evidence shows the effectiveness of authorities’ immediate and consistent response to stop bullying behavior. Social network analyses of online community Twitter may provide timely insights to reduce bullying behavior during the COVID-19 outbreak. The purpose of study is to apply social network analyses on Korean Tweets as a foundation for insights about early detection and preventing bullying and verbal abuse dissemination during the COVID-19 outbreak. We randomly extracted Korean Tweets mentioning COVID-19 and its related terms (n= 114,206 Tweets) from Tweet corpora collected daily via nCapture in the midst of COVID-19 outbreak (Feb 18 to Mar 2, 2020). We applied a clustering algorithm to detect networking groups of spreading bullying messages from the Tweet corpus after preprocessing using ORA. The authors visualized social networks of bullying and verbal violence among Korean Twitter users. A total of 48,714 Tweets (0.26%) included bullying or abusive terms which demean or insult a person or a group of people: 미* (n= 17,196, 35.3%), 새* (n=16,303, 33.5%), *놈 (n=9500, 19.5%), 중국*/짱* (n= 3,423, 4.8%), 친일*(n= 1,476, 3.0%), 개*(n=788, 1.6%), 씨* (n= 28, 0.1%). 28,690 Korean Twitter users participated bullying behaviors by creating or disseminating/retweeting Tweet messages that demean or insult a person or a certain country (0.26%). Sixteen distinct groups, who facilitated bullying behavior (> 50 times retweeted) within Twitter community, were detected (Newman clustering modularity: 0.63). Social network analysis of Twitter may be useful for leaders, stakeholders and authorities to early detect bullying and verbal violence and promptly take action on preventing spread of bullying behavior in order to establish a safe and clean social media environment during the COVID-19 outbreak.