[1T4-GS-4] Web intelligence

[1T4-GS-4-02] Classification of Agitation Tweets for the Purpose of Detecting "Agitation" Tweets in SNS

〇Masaki Tomita¹, Hajime Murai¹ (1. Future University Hakodate)

[[Online]]

Keywords:SNS, Natural Language Processing, Agitation

In recent years, trouble on social networking services has become an issue. One of the causes is "agitation. However, "agitation" in SNS has not been defined in detail, and accurate detection has not been achieved. In this study, we classify agitation expressions in order to achieve accurate detection of "agitation" in SNS. As target data, we collected tweets that were judged by the analyst to be agitation using the Twitter API, extracted and annotated the means, intentions, and topics considered to be constituent elements. The χ-square test and factor analysis were conducted using the statistical data of the components included in each tweet. In the factor analysis, factors such as promotion, judgment, slander, mounting, and inducement were obtained. The obtained results show the characteristics of the components of "agitation" and their relationships in SNS, and are considered to be useful for classifying agitated tweets.