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Analisis Topik Modelling Terhadap Penggunaan Sosial Media Twitter oleh Pejabat Negara

Patmawati Patmawati, Muhammad Yusuf

2021Building of Informatics Technology and Science (BITS)14 citationsDOIOpen Access PDF

Abstract

Social media is experiencing rapid development until now. Social media makes it easy for humans to be able to connect with one another. One of the social media that is widely used is Twitter. The ease of use makes social media widely used among the public, including state officials. State officials use Twitter to convey policies, opinions and interact with the public. By conducting a topic analysis of tweets shared by state officials, we can find out the relevant topics discussed by state officials. We can find out the focus of attention of state officials through topic modeling. Latent Dirichlet Allocation (LDA) is a topic modeling method that finds certain patterns in documents and produces several different topics. Tweets from the @jokowi account are collected using a scraping technique. The results of the tweet collection are then preprocessed for further analysis using the Latent Dirichlet Allocation (LDA) method. The results of the analysis model are evaluated using perplexity calculations and coherence scores. The evaluation of the model resulted in a perplexity value of -8.069 and a coherence score of 0.375 for a total of 7. This shows that the model used is good for analyzing and finding topics in tweets of state officials.

Topics & Concepts

PerplexityLatent Dirichlet allocationTopic modelSocial mediaCoherence (philosophical gambling strategy)Computer scienceState (computer science)Artificial intelligenceWorld Wide WebStatisticsLanguage modelMathematicsAlgorithmEdcuational Technology SystemsData Mining and Machine Learning ApplicationsInformation Retrieval and Data Mining
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