[1I4-GS-4c] Webインテリジェンス：SNS

[1I4-GS-4c-03] Verification of Slander Factors on SNS by Using Aggressive Post Simulation Model

〇Kouki Isoya¹, Ei-Ichi Osawa² (1. Graduate School of Future University Hakodate, 2. Future University Hakodate)

Keywords:Simulation, Social Media, Decision Making ・ Consensus Building

While SNS has been widely used in recent years, there are offensive posts such as slander are made, which has become a problem. Therefore, it is necessary to devise effective countermeasures after understanding the characteristics of aggressive posts such as slander. The purpose of this study is to build a model that can accurately express the dynamics of occurrence and convergence of aggressive posts such as slander on themes that divide opinions, and analyze their characteristics. The model defines five states for each user: neutral, agree, agree and aggressive, disagree, and disagree and aggressive, and is set to take into account the influence of neighboring users on state transitions. As a result of measuring the time-series distance between the development of user who is in the aggressive state on Twitter and the development of user who is in the aggressive state in the model by DTW, the proposed model is 4.493 for agree and aggressive, 7.443 for disagree and aggressive. Therefore, it was possible to construct a model with a high degree of similarity compared to 132.2 and 170.0 when each state was randomly transitioned. It was also shown that the cumulative ratio of the total number of users in aggressive states decreases when the influence of users that aggressive and have same opinion is suppressed.