Pandemic Fatigue: An Analysis of Twitter Users’ Sentiments Against the COVID-19 in Indonesia

https://doi.org/10.22146/jpsi.71979

Dina Arifka(1*), Muhammad Naufal Hakim(2), Adib Siddhi Adhipta(3), Ketut Shri Satya Yogananda(4), Rania Salsabila(5), Ridi Ferdiana(6)

(1) Faculty of Psychology, Universitas Gadjah Mada
(2) Faculty of Engineering, Universitas Gadjah Mada, Indonesia,
(3) Faculty of Engineering, Universitas Gadjah Mada, Indonesia,
(4) Faculty of Medicine Public Health and Nursing, Universitas Gadjah Mada,
(5) Faculty of Cultural Sciences, Universitas Gadjah Mada
(6) Faculty of Engineering, Universitas Gadjah Mada
(*) Corresponding Author

Abstract


Indonesian society is undergoing a shift of behavioral patterns towards the coronavirus (COVID) 19 indicating the symptoms of the pandemic fatigue phenomenon. Pandemic fatigue is defined as a gradual demotivation to adhere to recommended protective behaviors. Pandemic fatigue might reduce the effectiveness of health protocols and accelerate the spread of the virus. This study aims to examine the pandemic fatigue sentiment of Indonesian twitter-users chronologically and the factors causing the development of pandemic fatigue sentiment. The method of this study includes digital ethnographic theory using sentiment analysis based on the Valence Aware Dictionary for Sentiment Reasoning (VADER) algorithm and topic modelling using Latent Dirichlet Allocation (LDA) analysis. The results showed a pattern of sentiment degression towards health protocols indicating the pandemic fatigue phenomenon. The factors causing the sentiment degression were influenced by three themes: (1) public criticism of the government's efforts to handle the spread of COVID-19, (2) experience in implementing health protocols, and (3) statements that against the government’s efforts to handle the spread of COVID-19. Based on the results of sentiment analysis and topic modelling, this study presents a public policy design referencing the World Health Organization (WHO) framework for community reinvigoration in the midst of pandemic fatigue that could be used for the government to undertake broader reforms to public health and social care for Indonesian society.

Keywords


pandemic fatigue; twitter; etnografi digital

Full Text:

PDF


References

Bansilal, S. (2017). The application of the percentage change calculation in the context of inflation in mathematical literacy. Pythagoras.38(1), 1-11.

Boon-Itt, S. dan Skunkan, Y. (2020). Public perception of the COVID-19 pandemic on twitter: sentiment analysis and topic modeling study. JMIR Public Health Surveill.6(4), 1-17.

Budiharto, W. dan Meiliana, M. (2018). Prediction and analysis of indonesia presidential election from Twitter using sentiment analysis. Journal of Big Data.5(51), 1-10.

Christian, A.C.S., dan Sai'd, M. (2021). Public obedience to health protocols during COVID-19 pandemic in Indonesia: A perspective from health belief model theory. Journal of Social Science and Humanities, 11(2), 1-11.

Disemadi, H. dan Handika, D. (2020). Community compliance with the covid-19 protocol hygiene policy in Klaten Regency Indonesia. Legality: Jurnal Ilmiah Hukum.28(2), 121-133.

Demirtaş-Madran, H., (2021). Accepting restrictions and compliance with recommended preventive behaviors for COVID-19: a discussion based on the key approaches and current research on fear appeals. Frontiers in Psychology, 12.

Echoru, I., Kasozi, k., Usman, I., Ssempijja, F., Ayikobua, E., Mujinya, R., Ajambo, P., Matama, K., Lemuel, A., Tabakwot, J., Aruwa, J., Kegoye, E., Segun, O., Adeoye, A., Archibong, V., Nankya, V., Henry, S., Onongha, C. and Welburn, S., (2022). Religion influences community adherence to COVID-19 guidelines in Uganda. Termo Fisher Scientific, 1-11.

Góralska, M. (2020). Anthropology from home. Anthropology in Action.27(1), 46-52.

Halimatunnisa’, M. Lestari, P. dan Ulfiana, E. (2021). Beliefs and the correlation with protection health behaviors covid-19: A systematic review. Jurnal Keperawatan. 13(2), 605-614.

Ibrahim, A. Hassaballah, M. Ali, A. Nam, Y. dan Ibrahim, I. (2021). COVID19 outbreak: A hierarchical framework for user sentiment analysis. Computers, Materials & Continua. 70(2), 2507-2524.

Janis, I. L. (1967). Effects of fear arousal on attitude change: recent developments in theory and experimental research. Adv. Exp. Soc. Psychol. 3, 166–224.

Machmud, M., Irawan, B., Karinda, K., Susilo, J., Salahudin. (2021). Analysis of the intensity of communication and coordination of government officials on twitter social media during the COVID-19 handling in Indonesia. Academic Journal of Interdisciplanary Studies, 10(3), 319-334.

Mansdorf, I. J. (2020). Enforcing compliance with COVID-19 pandemic restrictions: Psychological aspects of a national security threat. Jerusalem Center for Public Affairs, 20(3).

Morea, P. (2021). Post Covid-19 pandemic scenarios in an unequal world challenges for sustainable development in Latin America. World.2(1), 1-14.

Moussaoui, L. Ofosu, N., dan Desrichard, O. (2020). Social psychological correlates of protective behaviours in the COVID‐19 outbreak: Evidence and recommendations from a nationally representative sample. Applied Psychology: Health and Well-Being.12(4), 1183-1204.

Nasukawa, T., dan Yi, J. (2003). Sentiment analysis. Proceedings of the international conference on Knowledge capture - K-CAP '03. 70-77.

Pagliaro, S., Sacchi, S., Pacilli, M., Brambilla, M., Lionetti, F., & Bettache, K. dkk. (2021). Trust predicts COVID-19 prescribed and discretionary behavioral intentions in 23 countries. PLOS ONE, 16(3), e0248334.

Petherick, A. Goldszmidt, R. Andrade, E. Furst, R. Hale, T. Pott, A. dan Wood, A. (2021). A worldwide assessment of changes in adherence to COVID-19 protective behaviours and hypothesized pandemic fatigue. Nature Human Behaviour.5(9), 1145-1160.

Rufai, S. and Bunce, C. (2020). World leaders’ usage of twitter in response to the COVID-19 pandemic: A content analysis. Journal of Public Health.42(3), 510-516.

Ridhwan, K.M. dan Hargreaves, C.A. (2021). Leveraging Twitter data to understand public sentiment for the COVID-19 outbreak in Singapore. International Journal of Information Management Data Insights.1(2), 100021.

Rypdal, K. Bianchi, F. dan Rypdal, M. (2020). Intervention fatigue is the primary cause of strong secondary waves in the covid-19 pandemic. International Journal of Environmental Research and Public Health. 17(9592), 1-17.

Satuan Tugas Penanganan COVID-19. (2021). Monitoring kepatuhan protokol kesehatan di 34 provinsi Indonesia (update per 3 Januari 2021). URL: https://covid19.go.id/p/berita/monitoring-kepatuhan-protokol-kesehatan-di-34-provinsi-indonesia-update-3-januari-2021. Diakses tanggal 19 Maret 2021.

Stevem, K. Ghanima, W. Olsen, K. Gilboe, M. dan Einvik, G. (2021). Prevalence and determinant of fatigue after COVID-19 in non-hospitalized subjects: a population-based study. International Journal of Environmental Research and Public Health. 18(4), 1-11.

World Health Organization. (2020). Pandemic Fatigue Reinvigorating The Public to Prevent COVID-19. WHO Regional Office for Europe. UN City. Denmark.

WHO dan UNICEF. (2020). Community-based Health Care, Including Outreach and Campaigns, in the Context of the COVID-19 Pandemic. World Health Organization and the United Nations Children’s Fund (UNICEF). Geneva. Switzerland.

Williams, S., Armitage, C., Tampe, T. and Dienes, K., 2021. Public perceptions of non-adherence to pandemic protection measures by self and others: A study of COVID-19 in the United Kingdom. PLOS ONE, 16(10), 1-18.



DOI: https://doi.org/10.22146/jpsi.71979

Article Metrics

Abstract views : 3682 | views : 1643

Refbacks

  • There are currently no refbacks.




Copyright (c) 2022 Jurnal Psikologi

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Published by Faculty of Psychology Universitas Gadjah Mada, Indonesia Building D 6th Floor No. D-606. Jl. Sosio Humaniora No. 1, Bulaksumur Yogyakarta, 55281
Email: jurnalpsikologi@ugm.ac.id
Phone/whatsApp: +6289527548628

Web
Analytics Made Easy - StatCounter View My Stats