Twitter can inform us what people are currently talking about and what is happening in the world. In the movement to free Reuters journalists (#FreeWaLoneKyawSoeOo) who were detained in Myanmar on Dec. 12, 2017, social media is utilized to express feeling and opinion. In social media, the rise of a trending topic leads to appear the temporal emergence of a set of users currently interested in that topic. Finding the influential person and measuring their influence are interesting problems in a social network. At first, the person who has many followers are more influence others. However, the influence score does not depend on the number of followers. In this study, we apply Social Network Analysis (SNA) to extract knowledge from social media data. We create a trending topic network graph related to an event. This graph was created by extracting relationships between users who are related to a given trending topic while they processed reply, mention or retweet operations. We used centrality measurement approaches and link analysis approach to find influential users. By using interaction relationships between users, we verify that PageRank can detect more influential users than other centrality measurement approaches. The result of this study will help to understand the structure of the network and also detect the most influential users.
Myat Mon Oo, May Thu Lwin
Semantic Web and Web Services Lab, Faculty of Computer Science
Semantic Web and Web Services
International Conference on Intelligence Science, ICIS 2019: Computer and Information Science pp 163-177
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