Sentiment analysis of twitter data related to Rinca Island development using Doc2Vec and SVM and logistic regression as classifier

Tirta Hema Jaya Hidayat, Yova Ruldeviyani, Achmad Rizki Aditama, Gusti Raditia Madya, Ade Wija Nugraha, Muhammad Wijaya Adisaputra

Research output: Contribution to journalConference articlepeer-review

10 Citations (Scopus)

Abstract

Development on Rinca Island by the Indonesian Government has received a lot of reaction from the community. Masses expressed their opinion through social media, especially Twitter regarding the matter. The research was conducted to analyze the public's sentiment about this development which was divided into three categories: pro, contra, and neutral. There are two Doc2Vec models used in this research, the distributed model, and the distributed bag of words, and using support vector machines and logistic regression as classifiers. Each combination of the models and classifier has an accuracy rate above 75% and shows that almost all are against the development of Rinca Island.

Original languageEnglish
Pages (from-to)660-667
Number of pages8
JournalProcedia Computer Science
Volume197
DOIs
Publication statusPublished - 2021
Event6th Information Systems International Conference, ISICO 2021 - Virtual, Online, Italy
Duration: 7 Aug 20218 Aug 2021

Keywords

  • Doc2Vec
  • Logistic regression
  • Natural languange processing
  • Sentiment analysis
  • Support vector machine

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