Performance of DKI Jakarta governor and vice governor on 2017-2018 based on sentiment analysis using twitter and instagram data

Bintang Glenn Julian, Indra Budi, Dipta Tanaya

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

2 Citations (Scopus)

Abstract

Sentiment analysis is one of the topics that recently getting more popular on political field or government-related things. Analyzing citizens' view of the government, including Governor and Vice Governor of DKI Jakarta for 2017-2022 period, is one of tasks that can be done using sentiment analysis. Data related to that topic ar e gathered from Twitter and Instagram for further analysis. N-gram, emoji, and all-caps is used as features to classify sentiment of each item. Based on the experiment, those features can help to increase classification performance. Naïve Bayes, Random Forest, and SVM algorithm are compared to select the best algorithm out of those three algorithms. Based on the experiment, SVM get the best result with highest accuracy and F1-score on both domains. The result of the classification shows that citizens tend to have neutral view on Governor and Vice Governor of DKI Jakarta for 2017-2022 period on their first year of governance. In addition, there are more positives than negatives on citizens' view.

Original languageEnglish
Title of host publicationProceedings of the 2019 2nd International Conference on Data Science and Information Technology, DSIT 2019
PublisherAssociation for Computing Machinery
Pages122-127
Number of pages6
ISBN (Electronic)9781450371414
DOIs
Publication statusPublished - 19 Jul 2019
Event2nd International Conference on Data Science and Information Technology, DSIT 2019 - Seoul, Korea, Republic of
Duration: 19 Jul 201921 Jul 2019

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2nd International Conference on Data Science and Information Technology, DSIT 2019
Country/TerritoryKorea, Republic of
CitySeoul
Period19/07/1921/07/19

Keywords

  • All-caps
  • Emoji
  • Governor
  • N-gram
  • Sentiment analysis

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