Community Understanding of the Importance of Social Distancing Using Sentiment Analysis in Twitter

Tri Buana Tungga Dewi; Nadina Adelia Indrawan; Indra Budi; Aris Budi Santoso; Prabu Kresna Putra

doi:10.1109/IC2IE50715.2020.9274589

Community Understanding of the Importance of Social Distancing Using Sentiment Analysis in Twitter

Tri Buana Tungga Dewi, Nadina Adelia Indrawan, Indra Budi, Aris Budi Santoso, Prabu Kresna Putra

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Citations (Scopus)

Abstract

The government may use social media, such as Twitter, to socialize a policy or a program to society. We may predict whether a program is successful or not by analyzing the sentiment of societies towards such program or communities through their tweets. The latest program of Indonesia's government during the COVID-19 pandemic is to make people do social distancing. It is socialized using the hashtag of stay at home appeal (#dirumahaja). The objective of this study is to analyze the understanding of societies regarding this program through people's tweet. We compared two classification algorithms (Naive Bayes and Random Forest), using tokenization and unigram features to build classification model of tweet sentiment. The tweets that included some hashtags regarding social distancing program, were collected with 5101 tweets in total. The highest accuracy is obtained using the Random Forest algorithm and term weighting feature, which yielded 95.98%. From the model we found that the number of positive sentiments is greater than the negative sentiment. Which can be concluded that the societies are understand and agree to the social distancing program.

Original language	English
Title of host publication	2020 3rd International Conference on Computer and Informatics Engineering, IC2IE 2020
Editors	Indra Hermawan, Muhammad Yusuf Bagus Rasyidin, Malisa Huzaifa, Iklima Ermis Ismail, Asep Taufik Muharram, Anggi Mardiyono, Noorlela Marcheeta, Dewi Kurniawati, Ade Rahma Yuly, Ariawan Andi Suhanda
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	336-341
Number of pages	6
ISBN (Electronic)	9781728182476
DOIs	https://doi.org/10.1109/IC2IE50715.2020.9274589
Publication status	Published - 15 Sept 2020
Event	3rd International Conference on Computer and Informatics Engineering, IC2IE 2020 - Depok, Indonesia Duration: 15 Sept 2020 → 16 Sept 2020

Publication series

Name	2020 3rd International Conference on Computer and Informatics Engineering, IC2IE 2020

Conference

Conference	3rd International Conference on Computer and Informatics Engineering, IC2IE 2020
Country/Territory	Indonesia
City	Depok
Period	15/09/20 → 16/09/20

Keywords

classification
COVID-19
naÏve Bayes
random forest
sentiment analysis
social appeal

Access to Document

10.1109/IC2IE50715.2020.9274589

Cite this

Dewi, T. B. T., Indrawan, N. A., Budi, I., Santoso, A. B., & Putra, P. K. (2020). Community Understanding of the Importance of Social Distancing Using Sentiment Analysis in Twitter. In I. Hermawan, M. Y. B. Rasyidin, M. Huzaifa, I. Ermis Ismail, A. T. Muharram, A. Mardiyono, N. Marcheeta, D. Kurniawati, A. R. Yuly, & A. A. Suhanda (Eds.), 2020 3rd International Conference on Computer and Informatics Engineering, IC2IE 2020 (pp. 336-341). Article 9274589 (2020 3rd International Conference on Computer and Informatics Engineering, IC2IE 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IC2IE50715.2020.9274589

Dewi, Tri Buana Tungga ; Indrawan, Nadina Adelia ; Budi, Indra et al. / Community Understanding of the Importance of Social Distancing Using Sentiment Analysis in Twitter. 2020 3rd International Conference on Computer and Informatics Engineering, IC2IE 2020. editor / Indra Hermawan ; Muhammad Yusuf Bagus Rasyidin ; Malisa Huzaifa ; Iklima Ermis Ismail ; Asep Taufik Muharram ; Anggi Mardiyono ; Noorlela Marcheeta ; Dewi Kurniawati ; Ade Rahma Yuly ; Ariawan Andi Suhanda. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 336-341 (2020 3rd International Conference on Computer and Informatics Engineering, IC2IE 2020).

@inproceedings{32926c0a829e4a389625e214d9b24683,

title = "Community Understanding of the Importance of Social Distancing Using Sentiment Analysis in Twitter",

abstract = "The government may use social media, such as Twitter, to socialize a policy or a program to society. We may predict whether a program is successful or not by analyzing the sentiment of societies towards such program or communities through their tweets. The latest program of Indonesia's government during the COVID-19 pandemic is to make people do social distancing. It is socialized using the hashtag of stay at home appeal (#dirumahaja). The objective of this study is to analyze the understanding of societies regarding this program through people's tweet. We compared two classification algorithms (Naive Bayes and Random Forest), using tokenization and unigram features to build classification model of tweet sentiment. The tweets that included some hashtags regarding social distancing program, were collected with 5101 tweets in total. The highest accuracy is obtained using the Random Forest algorithm and term weighting feature, which yielded 95.98%. From the model we found that the number of positive sentiments is greater than the negative sentiment. Which can be concluded that the societies are understand and agree to the social distancing program. ",

keywords = "classification, COVID-19, na{\"I}ve Bayes, random forest, sentiment analysis, social appeal",

author = "Dewi, {Tri Buana Tungga} and Indrawan, {Nadina Adelia} and Indra Budi and Santoso, {Aris Budi} and Putra, {Prabu Kresna}",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 3rd International Conference on Computer and Informatics Engineering, IC2IE 2020 ; Conference date: 15-09-2020 Through 16-09-2020",

year = "2020",

month = sep,

day = "15",

doi = "10.1109/IC2IE50715.2020.9274589",

language = "English",

series = "2020 3rd International Conference on Computer and Informatics Engineering, IC2IE 2020",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "336--341",

editor = "Indra Hermawan and Rasyidin, {Muhammad Yusuf Bagus} and Malisa Huzaifa and {Ermis Ismail}, Iklima and Muharram, {Asep Taufik} and Anggi Mardiyono and Noorlela Marcheeta and Dewi Kurniawati and Yuly, {Ade Rahma} and Suhanda, {Ariawan Andi}",

booktitle = "2020 3rd International Conference on Computer and Informatics Engineering, IC2IE 2020",

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Dewi, TBT, Indrawan, NA, Budi, I, Santoso, AB & Putra, PK 2020, Community Understanding of the Importance of Social Distancing Using Sentiment Analysis in Twitter. in I Hermawan, MYB Rasyidin, M Huzaifa, I Ermis Ismail, AT Muharram, A Mardiyono, N Marcheeta, D Kurniawati, AR Yuly & AA Suhanda (eds), 2020 3rd International Conference on Computer and Informatics Engineering, IC2IE 2020., 9274589, 2020 3rd International Conference on Computer and Informatics Engineering, IC2IE 2020, Institute of Electrical and Electronics Engineers Inc., pp. 336-341, 3rd International Conference on Computer and Informatics Engineering, IC2IE 2020, Depok, Indonesia, 15/09/20. https://doi.org/10.1109/IC2IE50715.2020.9274589

Community Understanding of the Importance of Social Distancing Using Sentiment Analysis in Twitter. / Dewi, Tri Buana Tungga; Indrawan, Nadina Adelia; Budi, Indra et al.
2020 3rd International Conference on Computer and Informatics Engineering, IC2IE 2020. ed. / Indra Hermawan; Muhammad Yusuf Bagus Rasyidin; Malisa Huzaifa; Iklima Ermis Ismail; Asep Taufik Muharram; Anggi Mardiyono; Noorlela Marcheeta; Dewi Kurniawati; Ade Rahma Yuly; Ariawan Andi Suhanda. Institute of Electrical and Electronics Engineers Inc., 2020. p. 336-341 9274589 (2020 3rd International Conference on Computer and Informatics Engineering, IC2IE 2020).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Community Understanding of the Importance of Social Distancing Using Sentiment Analysis in Twitter

AU - Dewi, Tri Buana Tungga

AU - Indrawan, Nadina Adelia

AU - Budi, Indra

AU - Santoso, Aris Budi

AU - Putra, Prabu Kresna

PY - 2020/9/15

Y1 - 2020/9/15

N2 - The government may use social media, such as Twitter, to socialize a policy or a program to society. We may predict whether a program is successful or not by analyzing the sentiment of societies towards such program or communities through their tweets. The latest program of Indonesia's government during the COVID-19 pandemic is to make people do social distancing. It is socialized using the hashtag of stay at home appeal (#dirumahaja). The objective of this study is to analyze the understanding of societies regarding this program through people's tweet. We compared two classification algorithms (Naive Bayes and Random Forest), using tokenization and unigram features to build classification model of tweet sentiment. The tweets that included some hashtags regarding social distancing program, were collected with 5101 tweets in total. The highest accuracy is obtained using the Random Forest algorithm and term weighting feature, which yielded 95.98%. From the model we found that the number of positive sentiments is greater than the negative sentiment. Which can be concluded that the societies are understand and agree to the social distancing program.

AB - The government may use social media, such as Twitter, to socialize a policy or a program to society. We may predict whether a program is successful or not by analyzing the sentiment of societies towards such program or communities through their tweets. The latest program of Indonesia's government during the COVID-19 pandemic is to make people do social distancing. It is socialized using the hashtag of stay at home appeal (#dirumahaja). The objective of this study is to analyze the understanding of societies regarding this program through people's tweet. We compared two classification algorithms (Naive Bayes and Random Forest), using tokenization and unigram features to build classification model of tweet sentiment. The tweets that included some hashtags regarding social distancing program, were collected with 5101 tweets in total. The highest accuracy is obtained using the Random Forest algorithm and term weighting feature, which yielded 95.98%. From the model we found that the number of positive sentiments is greater than the negative sentiment. Which can be concluded that the societies are understand and agree to the social distancing program.

KW - classification

KW - COVID-19

KW - naÏve Bayes

KW - random forest

KW - sentiment analysis

KW - social appeal

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DO - 10.1109/IC2IE50715.2020.9274589

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BT - 2020 3rd International Conference on Computer and Informatics Engineering, IC2IE 2020

A2 - Hermawan, Indra

A2 - Rasyidin, Muhammad Yusuf Bagus

A2 - Huzaifa, Malisa

A2 - Ermis Ismail, Iklima

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PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Dewi TBT, Indrawan NA, Budi I, Santoso AB, Putra PK. Community Understanding of the Importance of Social Distancing Using Sentiment Analysis in Twitter. In Hermawan I, Rasyidin MYB, Huzaifa M, Ermis Ismail I, Muharram AT, Mardiyono A, Marcheeta N, Kurniawati D, Yuly AR, Suhanda AA, editors, 2020 3rd International Conference on Computer and Informatics Engineering, IC2IE 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 336-341. 9274589. (2020 3rd International Conference on Computer and Informatics Engineering, IC2IE 2020). doi: 10.1109/IC2IE50715.2020.9274589

Community Understanding of the Importance of Social Distancing Using Sentiment Analysis in Twitter

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Keywords

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