research-article

Performance of DKI Jakarta Governor and Vice Governor on 2017-2018 based on Sentiment Analysis using Twitter and Instagram Data

Authors:

Bintang Glenn Julian,

Indra Budi,

Dipta TanayaAuthors Info & Claims

DSIT 2019: Proceedings of the 2019 2nd International Conference on Data Science and Information Technology

Pages 122 - 127

https://doi.org/10.1145/3352411.3352431

Published: 19 July 2019 Publication History

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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 are 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.

References

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Cited By

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Al-Rawi AAl-Musalli ARigor P(2021)Networked Flak in CNN and Fox News Memes on InstagramDigital Journalism10.1080/21670811.2021.191697710:9(1464-1481)Online publication date: 27-May-2021
https://doi.org/10.1080/21670811.2021.1916977
Purnomo AAgustina ISeptianto ALiahmad Prasetyo Y(2020)Instagram Literature: Insights from Scientometric Application2020 International Conference on Information Management and Technology (ICIMTech)10.1109/ICIMTech50083.2020.9211115(583-587)Online publication date: Aug-2020
https://doi.org/10.1109/ICIMTech50083.2020.9211115

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Published In

DSIT 2019: Proceedings of the 2019 2nd International Conference on Data Science and Information Technology

July 2019

280 pages

ISBN:9781450371414

DOI:10.1145/3352411

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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The Hong Kong Polytechnic: The Hong Kong Polytechnic University
Natl University of Singapore: National University of Singapore

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 July 2019

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DSIT 2019

DSIT 2019: 2019 2nd International Conference on Data Science and Information Technology

July 19 - 21, 2019

Seoul, Republic of Korea

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DSIT 2019 Paper Acceptance Rate 43 of 95 submissions, 45%;

Overall Acceptance Rate 114 of 277 submissions, 41%

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Al-Rawi AAl-Musalli ARigor P(2021)Networked Flak in CNN and Fox News Memes on InstagramDigital Journalism10.1080/21670811.2021.191697710:9(1464-1481)Online publication date: 27-May-2021
https://doi.org/10.1080/21670811.2021.1916977
Purnomo AAgustina ISeptianto ALiahmad Prasetyo Y(2020)Instagram Literature: Insights from Scientometric Application2020 International Conference on Information Management and Technology (ICIMTech)10.1109/ICIMTech50083.2020.9211115(583-587)Online publication date: Aug-2020
https://doi.org/10.1109/ICIMTech50083.2020.9211115

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