DETECTION OF THE KEY ACTOR OF ISSUES SPREADING BASED ON SOCIAL NETWORK ANALYSIS IN TWITTER SOCIAL MEDIA (CASE STUDY COVID-19 ISSUES IN INDONESIA)

• Main Author: Joize Oroh, Audy
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/54513
• Institution: Institut Teknologi Bandung

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 excellence ultimately contributes to social media misuse and contributes 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 or followers. Detection of key actors is one of the obstacles to handling hate speech and fake news on Twitter. We use the centrality analysis algorithm with degree centrality, closeness centrality, betweenness centrality, and eigenvector centrality method to solve this problem. Also, we use sentiment value to find out the positive or negative value of the comments in the account post. The degree centrality, betweenness centrality, and eigenvector centrality algorithm results have shown that the user who has the most influence and becomes a key actor in the spread of the issue is a user with user_id 150589950. The sentiment analysis algorithm obtains the sentiment calculation results indicated by the number of tweets. 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.