Detection of the Key Actor of Issues Spreading Based on Social Network Analysis in Twitter Social Media

Abstract

With the development of today's society's communication facilities, social media becomes the most effective and efficient means of conveying information to other parties. Social media's advantages ultimately contribute to social media misuse and contribute to the emergence and development of hoaxes and hate speech. Online social media such as Twitter is the most widely used means of communication in cyberspace. The important issue with the spread of news on Twitter is the presence of key actors who often spread the issue and are accounts that influence social media. These accounts usually have a lot of followers. Detection of the key actors is one of the obstacles to handling hate speech and fake news on Twitter. It can be solved using a centrality analysis algorithm with degree centrality, closeness centrality, betweenness centrality, and eigenvector centrality method to detect the key actor. Also, sentiment value is used to determine the positive or negative value of the comments' comments in the account post. The analysis of degree centrality algorithms, betweenness centrality, and eigenvector centrality has shown that the user who has the most influence and becomes a key actor in the spread of the issue is the user with user_id 150589950. The sentiment analysis algorithm obtained the sentiment calculation results shown by the tweet amount. The most influential users in the spread of tweets can be seen from the number of tweets that can be found from the tweet amount.