Sentiment Analysis of Indonesians Response to Influencer in Social Media

Syafi Muhammad Tauhid, Yova Ruldeviyani

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Social media as a space for information and thought exchange has many users who have outsized influence towards other users. Users with such influence are known by the term 'influencers'. Their influence on social media mainly conveyed in the content they share, either in texts or images form. Such influence become an important aspect of societal life since majority of citizens are now social media user. This research analyzes best classification method to predict the sentiment contained in the response to contents shared by Indonesian influencer Fiersa Besari and Keanu in Twitter. The data used are tweets and comments in Bahasa Indonesia, gathered from Twitter API and cleaned up. The final dataset consists of 3,243 tweets with manual labeling of sentiment. The classification algorithm considered in this research are Naïve Bayes, Support Vector Machine (SVM), Logistic Regression, and Decision Tree. The main result of this research is that Naïve Bayes classification method has the best F-Score performance compared with other methods, with TP Rate for Fiersa Besari 88% and Keanu 86% & TN Rate for Fiersa Besari 76% and Keanu 60%.

Original languageEnglish
Title of host publication7th International Conference on Information Technology, Computer, and Electrical Engineering, ICITACEE 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages90-95
Number of pages6
ISBN (Electronic)9781728172255
DOIs
Publication statusPublished - 24 Sep 2020
Event7th International Conference on Information Technology, Computer, and Electrical Engineering, ICITACEE 2020 - Semarang, Indonesia
Duration: 24 Sep 202025 Sep 2020

Publication series

Name7th International Conference on Information Technology, Computer, and Electrical Engineering, ICITACEE 2020 - Proceedings

Conference

Conference7th International Conference on Information Technology, Computer, and Electrical Engineering, ICITACEE 2020
Country/TerritoryIndonesia
CitySemarang
Period24/09/2025/09/20

Keywords

  • machine learning
  • sentiment analysis
  • social media
  • text classification

Fingerprint

Dive into the research topics of 'Sentiment Analysis of Indonesians Response to Influencer in Social Media'. Together they form a unique fingerprint.

Cite this