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

机译:基于社交网络分析在Twitter社交媒体中的发布散布关键演员的检测

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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.
机译:随着当今社会的通信设施的发展,社交媒体成为将信息传达给其他方的最有效和最有效的手段。社交媒体的优势最终促进了社交媒体滥用,有助于出现恶作剧和仇恨言论的出现和发展。 Twitter等在线社交媒体是网络空间中最广泛使用的通信手段。关于Twitter的新闻传播的重要问题是存在经常传播该问题的主要演员,并且是影响社交媒体的账户。这些帐户通常有很多粉丝。检测关键演员是处理Twitter上的仇恨言论和假新闻的障碍之一。可以使用具有程度中心,密闭中心,中心中心和特征向量的中心中心的中心分性分析算法来解决,以检测关键演员。此外,情绪值用于确定帐户帖子中评论评论的正值或负值。对程度中心算法,中心性和特征传感器中心的分析表明,具有最大影响和成为问题传播中的关键演员的用户是具有User_ID 150589950的用户。情绪分析算法获得了情绪计算结果由推文金额显示。可以从推文金额中找到的推文的数量来看推文的传播中最有影响力的用户。

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