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Volume 13
Issue 10
10.3390/info13100484
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Article

A Semi-Supervised Approach to Sentiment Analysis of Tweets during the 2022 Philippine Presidential Election

by
Julio Jerison E. Macrohon
1,*,
Charlyn Nayve Villavicencio
1,2,
X. Alphonse Inbaraj
1 and
Jyh-Horng Jeng
1
1
Department of Information Engineering, I-Shou University, Kaohsiung City 84001, Taiwan
2
College of Information and Communications Technology, Bulacan State University, Bulacan 3000, Philippines
*
Author to whom correspondence should be addressed.
Information 2022, 13(10), 484; https://doi.org/10.3390/info13100484
Submission received: 13 September 2022 / Revised: 27 September 2022 / Accepted: 7 October 2022 / Published: 9 October 2022
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Abstract

With the increasing popularity of Twitter as both a social media platform and a data source for companies, decision makers, advertisers, and even researchers alike, data have been so massive that manual labeling is no longer feasible. This research uses a semi-supervised approach to sentiment analysis of both English and Tagalog tweets using a base classifier. In this study involving the Philippines, where social media played a central role in the campaign of both candidates, the tweets during the widely contested race between the son of the Philippines’ former President and Dictator, and the outgoing Vice President of the Philippines were used. Using Natural Language Processing techniques, these tweets were annotated, processed, and trained to classify both English and Tagalog tweets into three polarities: positive, neutral, and negative. Through the Self-Training with Multinomial Naïve Bayes as base classifier with 30% unlabeled data, the results yielded an accuracy of 84.83%, which outweighs other studies using Twitter data from the Philippines.
Keywords: 2022 Philippine Presidential Election; semi-supervised learning; Natural Language Processing; sentiment analysis; Python; social media; Twitter; tweets 2022 Philippine Presidential Election; semi-supervised learning; Natural Language Processing; sentiment analysis; Python; social media; Twitter; tweets

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MDPI and ACS Style

Macrohon, J.J.E.; Villavicencio, C.N.; Inbaraj, X.A.; Jeng, J.-H. A Semi-Supervised Approach to Sentiment Analysis of Tweets during the 2022 Philippine Presidential Election. Information 2022, 13, 484. https://doi.org/10.3390/info13100484

AMA Style

Macrohon JJE, Villavicencio CN, Inbaraj XA, Jeng J-H. A Semi-Supervised Approach to Sentiment Analysis of Tweets during the 2022 Philippine Presidential Election. Information. 2022; 13(10):484. https://doi.org/10.3390/info13100484

Chicago/Turabian Style

Macrohon, Julio Jerison E., Charlyn Nayve Villavicencio, X. Alphonse Inbaraj, and Jyh-Horng Jeng. 2022. "A Semi-Supervised Approach to Sentiment Analysis of Tweets during the 2022 Philippine Presidential Election" Information 13, no. 10: 484. https://doi.org/10.3390/info13100484

APA Style

Macrohon, J. J. E., Villavicencio, C. N., Inbaraj, X. A., & Jeng, J.-H. (2022). A Semi-Supervised Approach to Sentiment Analysis of Tweets during the 2022 Philippine Presidential Election. Information, 13(10), 484. https://doi.org/10.3390/info13100484

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