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Analyzing Netizens’Perceptions Towards Indonesian Presidential Candidates Using Topic Modeling Approach

机译:利用主题建模方法分析向印度尼西亚总统候选人的网格化

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Over the past few years, Twitter has significantly grown as the microblogging platform.Millions of user use this platform to share their attitudes, views, and opinion on a daily basis.This phenomenon has been used to promote people's attention towards some event, such as 2019 Indonesian Presidential Election.In this study, we investigate people's online opinions towards the event through social media.The goal of the study is to discover frequent topics amongst netizens’tweets during the election campaign.We collected tweets containing the names of the candidates, then applied topic modelling approach using Latent Dirichlet Allocation(LDA)method to cluster the topics.Based on the experiment, the tweets are clustered into ten topics with different focuses e.g., a topic discusses the candidate's position towards sensitive issues, a topic about the community supports towards one presidential candidate.Our result shows that topic modelling approach can be used to analyse people's perception in social media towards an important event.
机译:在过去的几年里,Twitters在微博平台上显着发展。用户使用这个平台每天使用这个平台分享他们的态度,观点和意见。这一现象已被用来促进人们对一些事件的注意,如2019年印度尼西亚总统选举。我们通过社交媒体调查人们对活动的在线意见。该研究的目标是在选举活动期间发现Netizens'tweets之间的频繁主题。我们收集了包含候选人姓名的推文,然后应用主题建模方法使用潜在的Dirichlet分配(LDA)方法来聚类主题。基于实验,推文被聚集成10个具有不同焦点的主题,例如,一个主题讨论了候选人对敏感问题的职位,这是一个关于社区的主题支持一个总统候选人。我们的结果表明,主题建模方法可用于分析人们的看法在社交媒体上走向重要事件。

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