Tinjauan Analisis Sentimen Terkait COVID-19
DOI:
https://doi.org/10.57119/litdig.v3i1.118Keywords:
COVID-19, Emotion, Literature Review, Method, Sentiment AnalysisAbstract
The Covid-19 pandemic control policy has created public opinion on social media. The government controls sentiment so that people remain compliant with the policy. Several previous studies have analyzed sentiment with various approaches. This study aims to describe how to analyze sentiment related to the pandemic of earlier studies with a traditional literature review approach through the literature survey stage. The results of the review found various approaches to data collection and sentiment analysis that have been applied by previous studies and their challenges, as well as opportunities for further research.Downloads
References
Ahammad, T., 2024. Identifying hidden patterns of fake COVID-19 news: An in-depth sentiment analysis and topic modeling approach. Natural Language Processing Journal 6, 100053.
Anastasiou, D., Ballis, A., Drakos, K., 2022. Constructing a positive sentiment index for COVID-19: Evidence from G20 stock markets. International Review of Financial Analysis 81, 102111.
Cahyana, R., Fitriani, L., Setiawan, Y., Mahayana, D., 2024. Research on Online Hate Speech Detection from Popper and Kuhn’s Philosophical Perspective. litdig 2, 61–66. https://doi.org/10.57119/litdig.v2i2.96
Chakraborty, K., Bhatia, S., Bhattacharyya, S., Platos, J., Bag, R., Hassanien, A.E., 2020. Sentiment Analysis of COVID-19 tweets by Deep Learning Classifiers—A study to show how popularity is affecting accuracy in social media. Applied Soft Computing 97, 106754.
Costola, M., Nofer, M., Hinz, O., Pelizzon, L., 2020. Machine Learning Sentiment Analysis, COVID-19 News and Stock Market Reactions;(No. 288). Leibniz Institute for Financial Research SAFE.
Garcia, K., Berton, L., 2021. Topic detection and sentiment analysis in Twitter content related to COVID-19 from Brazil and the USA. Applied soft computing 101, 107057.
Garcia, M.B., 2020. Sentiment Analysis of Tweets on Coronavirus Disease 2019 (COVID-19) Pandemic from Metro Manila, Philippines. Cybernetics and Information Technologies 20, 141–155. https://doi.org/10.2478/cait-2020-0052
Gozal, A.G., Pranoto, H., Hasani, M.F., 2023. Sentiment analysis of the Indonesian community toward face-to-face learning during the Covid-19 pandemic. Procedia Computer Science 227, 398–405.
Lestandy, M., Abdurrahim, A., Syafa’ah, L., 2021. Analisis Sentimen Tweet Vaksin COVID-19 Menggunakan Recurrent Neural Network dan Naïve Bayes. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi) 5, 802–808.
Li, L., Mao, Y., Wang, Y., Ma, Z., 2022. How has airport service quality changed in the context of COVID-19: A data-driven crowdsourcing approach based on sentiment analysis. Journal of Air Transport Management 105, 102298.
Liu, A., Kam, J., Kwon, S., Shao, W., 2023. Monitoring the impact of climate extremes and COVID-19 on statewise sentiment alterations in water pollution complaints. NPJ Clean Water 6 (1): 29.
Malik, G., Singh, D., 2023. Twitter sentiment analysis: An estimation of the trends in tourism after the outbreak of the Covid-19 pandemic. European Journal of Tourism, Hospitality and Recreation 13, 40–48. https://doi.org/10.2478/ejthr-2023-0004
Manuaba, I.B.K., 2023. A sentiment analysis model for the COVID-19 vaccine in Indonesia using twitter API v2, TextBlob, and Googletrans. Procedia Computer Science 227, 1101–1110.
Melton, C.A., Olusanya, O.A., Ammar, N., Shaban-Nejad, A., 2021. Public sentiment analysis and topic modeling regarding COVID-19 vaccines on the Reddit social media platform: A call to action for strengthening vaccine confidence. Journal of Infection and Public Health 14, 1505–1512.
Nandal, N., Tanwar, R., Pathan, A.-S.K., 2023. Sentiment analysis based emotion extraction for COVID-19 using crawled tweets and global statistics for mental health. Procedia computer science 218, 949–958.
Navarro, J., Aguarón, J., Moreno-Jiménez, J.M., Turón, A., 2024. Social mood during the Covid-19 vaccination process in Spain. A sentiment analysis of tweets and social network leaders. Heliyon 10.
Pristiyono, Ritonga, M., Ihsan, M.A.A., Anjar, A., Rambe, F.H., 2021. Sentiment analysis of COVID-19 vaccine in Indonesia using Naïve Bayes Algorithm, in: IOP Conference Series: Materials Science and Engineering. IOP Publishing, p. 012045.
Samaras, L., García-Barriocanal, E., Sicilia, M.-A., 2023. Sentiment analysis of COVID-19 cases in Greece using Twitter data. Expert Systems with Applications 230, 120577.
Shofiya, C., Abidi, S., 2021. Sentiment analysis on COVID-19-related social distancing in Canada using Twitter data. International Journal of Environmental Research and Public Health 18, 5993.
Singh, M., Jakhar, A.K., Pandey, S., 2021. Sentiment analysis on the impact of coronavirus in social life using the BERT model. Soc. Netw. Anal. Min. 11, 33. https://doi.org/10.1007/s13278-021-00737-z
Xi, H., Zhang, C., Zhao, Y., He, S., 2022. Public emotional diffusion over COVID-19 related tweets posted by major public health agencies in the United States. Data Intelligence 4, 66–87.
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Copyright (c) 2024 Muhammad Affan Al Sidqi, Nabil Nur Afrizal, Novan Rodiansyah, Rinda Cahyana
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
