A Research On Determining the Common Characteristics of Trolls with Very High Interaction in the Covid-19 Anti-Vaccine Attitude

Social media has played an important role in the Covid-19 vaccine opposition during the pandemic process. In this regard, the messages that spread rapidly through the Twitter environment by means of trolls and bots have the potential to endanger human and public health. For this reason, the common features of troll accounts should be revealed. This will create awareness among users. Starting from this problem, first of all, bots were removed from anti-vaccine troll accounts and the interaction rate on the remaining ones was calculated. Then, the median of the relevant ratio was taken to determine the distribution of the interaction groups according to the interaction rate. Thus, 4 distributed interaction groups were identified as low-medium-high-very high. Finally, the differences between these interaction groups in various aspects -which are referred to as common features - were calculated with the Anova Test, thus revealing the status of those with very high interaction compared to other interaction groups. According to the results, anti -vaccine trolls tried to influence Twitter users by using ways such as tweeting a lot, having the potential to receive a large number of retweets, using a large number of hashtags, and spreading the posts over a wide time period. It is important to determine the common features in order for users to be able to observe the trolls in question and to act accordingly.