Sentiment Analysis of Twitter Data: Understanding Public Opinion before the 15th General Elections in Malaysia

Authors

DOI:

https://doi.org/10.60072/ijeissah.2024.V2i03.001

Abstract

Amid the ever-growing social media content, sentiment analysis is a technique that is necessary for analyzing public opinion. This paper aims to discover what sentiment prevailed and what reaction took place preceding the election. This paper also presents the results of a study that applied sentiment analysis to Twitter data relating to the 15th General Elections of Malaysia. This research reviews several sentiment analysis techniques based on Twitter data. Using the method of analyzing 1566 tweets, including re-tweets and replies, gathered between November 12th and November 18th, 2022, the findings give us an understanding of the level of emotions that were tweeted by the users of Twitter towards the 15th general election in Malaysia. The results indicate that the sentiments expressed in the analysed tweets are distributed as follows: slightly positive (41%), positive (31%), neutral (24%), and slightly negative (4%).

Keywords:

15th General Elections, Twitter, Sentiment Analysis, Tweets, Hashtags

References

Chaudhry, H. N., Javed, Y., Kulsoom, F., Mehmood, Z., Khan, Z. I., Shoaib, U., & Janjua, S. H. (2021). Sentiment analysis of before and after elections: Twitter data of us election 2020. Electronics, 10(17), 2082. https://doi.org/10.3390/electronics10172082

Chaturvedi, D., Jain, T., Mishra, A., & Kapoor, A. (2023). Sentiment Analysis of Twitter Data using Machine Learning: A Case Study of SVM Algorithm. https://doi.org/10.21203/rs.3.rs-2850627/v2

Chin, J. (2023). Anwar’s long walk to power: the 2022 Malaysian general elections. The Round Table, 112(1), 1-13. https://doi.org/10.1080/00358533.2023.2165303

Chung, N. N., Chew, L. Y., & Lai, C. H. (2016). Critical Transitions in Public Opinion: A Case Study of American Presidential Election. arXiv preprint arXiv:1610.05426. https://doi.org/10.48550/arXiv.1610.05426

El-Beltagy, S. R., & Ali, A. (2013, March). Open issues in the sentiment analysis of Arabic social media: A case study. In 2013 9th International Conference on Innovations in information technology (IIT) (pp. 215-220). IEEE. https://doi.org/10.1109/Innovations.2013.6544421

Flores-Ruiz, D., Elizondo-Salto, A., & Barroso-González, M. D. L. O. (2021). Using social media in tourist sentiment analysis: A case study of Andalusia during the COVID-19 pandemic. Sustainability, 13(7), 3836. https://doi.org/10.3390/su13073836

Fornacciari, P., Mordonini, M., & Tomaiuolo, M. (2015, June). A case-study for sentiment analysis on twitter. In WOA (pp. 53-58).

Hasan, A., Moin, S., Karim, A., & Shamshirband, S. (2018). Machine learning-based sentiment analysis for twitter accounts. Mathematical and computational applications, 23(1), 11. https://doi.org/10.3390/mca23010011

Iman Research. (2023). "Election Sentiments Analysis of Malaysia's 15th General Elections (GE15) FINAL REPORT." https://www.imanresearch.com/wp content/uploads/2023/01/Election-Sentiments-Analysis-of-Malaysias-15th-General-Elections-GE15-FINAL-REPORT.pdf.

Iglesias, C. A., & Moreno, A. (2019). Sentiment analysis for social media. Applied Sciences, 9(23), 5037. https://doi.org/10.3390/app9235037

Kauffmann, E., Peral, J., Gil, D., Ferrández, A., Sellers, R., & Mora, H. (2020). A framework for big data analytics in commercial social networks: A case study on sentiment analysis and fake review detection for marketing decision-making. Industrial Marketing Management, 90, 523-537 https://doi.org/10.1016/j.indmarman.2019.08.003

Kavitha, G., Saveen, B., & Imtiaz, N. (2018, December). Discovering public opinions by performing sentimental analysis on real time Twitter data. In 2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET) (pp. 1-4). IEEE. https://doi.org/10.1109/ICCSDET.2018.8821105

Kołczyńska, M., & Bürkner, P. C. (2024). Modeling public opinion over time: A simulation study of latent trend models. Journal of Survey Statistics and Methodology, 12(1), 130-154.] https://doi.org/10.1093/jssam/smad024

Lee, H. W. (2018). Using Twitter Hashtags to gauge real-time changes in public opinion: an examination of the 2016 US presidential election. In Social Informatics: 10th International Conference, SocInfo 2018, St. Petersburg, Russia, September 25-28, 2018, Proceedings, Part II 10 (pp. 168-175). Springer International Publishing. https://doi.org/10.1007/978-3-030-01159-8_16

Masch, L., & Gabriel, O. W. (2020). How emotional displays of political leaders shape citizen attitudes: The case of German Chancellor Angela Merkel. German Politics, 29(2), 158-179. https://doi.org/10.1080/09644008.2019.1657096

Mishra, P., Rajnish, R., & Kumar, P. (2016, October). Sentiment analysis of Twitter data: Case study on digital India. In 2016 International Conference on Information Technology (InCITe)-The Next Generation IT Summit on the Theme-Internet of Things: Connect your Worlds (pp. 148-153). IEEE. https://doi.org/10.1109/INCITE.2016.7857607

Moten, A. R. (2023). Research Note: The 15th General Elections in Malaysia. Contemporary Southeast Asia, 45(1), 111-127.

Ong, K. M. (2023). GE15: opening up new vistas for comparative research on Malaysian politics. The Round Table, 112(3), 335-336. https://doi.org/10.1080/00358533.2023.2219528

Rita, P., António, N., & Afonso, A. P. (2023). Social media discourse and voting decisions influence: sentiment analysis in tweets during an electoral period. Social Network Analysis and Mining, 13(1), 46.

Schmeller, M. (2023). Public Opinion in Emerson, D. B., & Laski, G. (Eds.). Democracies in America: Keywords for the 19th Century and Today (pp. 142-C12.S1). Oxford University Press. https://doi.org/10.1093/oso/9780198865698.003.0013

Shukri, S. E., Yaghi, R. I., Aljarah, I., & Alsawalqah, H. (2015, November). Twitter sentiment analysis: A case study in the automotive industry. In 2015 IEEE Jordan conference on applied electrical engineering and computing technologies (AEECT) (pp. 1-5). IEEE https://doi.org/10.1109/AEECT.2015.7360594

Published

17-08-2024

How to Cite

Abdul Same’e, S. . (2024). Sentiment Analysis of Twitter Data: Understanding Public Opinion before the 15th General Elections in Malaysia. International Journal of Emerging Issues in Social Science, Arts and Humanities ( IJEISSAH), 2(3), 1-11. https://doi.org/10.60072/ijeissah.2024.V2i03.001