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October 31, 2023
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March 22, 2024
Published
May 2, 2024
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Abstract

The COVID-19 pandemic has become a complicated problem faced by the world. The absence of specific antiviral drugs or vaccines at the beginning of the outbreak made the public health approach the primary strategy for preventing the spread of COVID-19. The lack of transparency at the start of the COVID-19 outbreak also led to public misinformation. WHO called it an infodemic, an excess of information, whether true or not, making it difficult for people to determine valid references. In Indonesia, misinformation on health matters is not a new difficulty and is in the top rank along with socio-political. The government utilizes social media to provide information to the citizens. Social media itself has a vital role in the infodemic as a medium for disseminating information, whether credible or not. The Indonesian FDA plays an essential role in conducting education through social media. This study aims to map the elements forming citizens' engagement in Indonesian FDA social media use, especially in disseminating information about the COVID-19 vaccine. This study uses a regression method with citizens' engagement (calculated from the number of likes and comments) as the dependent variable. Three independent variables form citizen engagement elements: media richness, content production, and content type defined by the government. The sentiment toward government Instagram posts was measured by analyzing citizens' comments using the dataset from InSet Semantic Lexicon. Based on negative binomial regression results, data obtained that the framework developed in this research was statistically significant in observing the phenomenon. Media richness and content production significantly affect citizens' engagement. On the other hand, original and informative content encourages more citizen engagement. Generally, public sentiment on Indonesian FDA Instagram content, both head office and regional offices, tends to be more positive than negative.

Keywords

Covid-19 Indonesian FDA Instagram social me BPOM COVID-19 Instagram media sosial

Article Details

How to Cite
Dharma, A. A. S. (2024). Exploring the Communication, Information, and Education Strategies of the Indonesian FDA for COVID-19 Vaccine Development. Eruditio : Indonesia Journal of Food and Drug Safety, 4(1), 17–32. https://doi.org/10.54384/eruditio.v4i1.179
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References

  1. Abdelsalam, H. M., Reddick, C. G., Gamal, S., & Al-shaar, A. (2013). Social media in Egyptian government websites: Presence, usage, and effectiveness. Government Information Quarterly, 30(4), 406–416. https://doi.org/10.1016/j.giq.2013.05.020
  2. Ahmad, A. R., & Murad, H. R. (2020). The impact of social media on panic during the COVID-19 pandemic in iraqi kurdistan: Online questionnaire study. Journal of Medical Internet Research, 22(5), 1–11. https://doi.org/10.2196/19556
  3. Ashraf, B. N. (2020). Economic impact of government interventions during the COVID-19 pandemic: International evidence from financial markets. Journal of Behavioral and Experimental Finance, 27, 100371. https://doi.org/https://doi.org/10.1016/j.jbef.2020.100371
  4. Azmi, A. F., & Budi, I. (2018). Exploring practices and engagement of Instagram by Indonesia Government Ministries. 2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE), 18–21. https://doi.org/10.1109/ICITEED.2018.8534799
  5. Bonsón, E., Royo, S., & Ratkai, M. (2014). Facebook Practices in Western European Municipalities: An Empirical Analysis of Activity and Citizens’ Engagement. Administration & Society, 49(3), 320–347. https://doi.org/10.1177/0095399714544945
  6. BPOM. (2020). Laporan Kinerja Badan Pengawas Obat dan Makanan Tahun 2019. https://www.pom.go.id/new/admin/dat/20200429/Laporan_Kinerja_2019_Badan_Pengawas_Obat_dan_Makanan.pdf
  7. Bridgman, A., Merkley, E., Loewen, P. J., Owen, T., Ruths, D., Teichmann, L., & Zhilin, O. (2020). The causes and consequences of COVID-19 misperceptions: Understanding the role of news and social media. Harvard Kennedy School Misinformation Review, 1(June), 1–18. https://doi.org/10.37016/mr-2020-028
  8. Chemela, M. S. R. (2019). The relation between content typology and consumer engagement in Instagram [Universidade Católica Portuguesa]. http://hdl.handle.net/10400.14/26921
  9. Chen, Q., Min, C., Zhang, W., Wang, G., Ma, X., & Evans, R. (2020). Unpacking the black box: How to promote citizen engagement through government social media during the COVID-19 crisis. Computers in Human Behavior, 110, 1–11. https://doi.org/https://doi.org/10.1016/j.chb.2020.106380
  10. Cinelli, M., Quattrociocchi, W., Galeazzi, A., Valensise, C. M., Brugnoli, E., Schmidt, A. L., Zola, P., Zollo, F., & Scala, A. (2020). The COVID-19 social media infodemic. Scientific Reports, 10(1), 16598. https://doi.org/10.1038/s41598-020-73510-5
  11. Dharma, A. A. S. (2023). New Public Service Sebagai Paradigma Administrasi Publik Pengawasan Obat dan Makanan. Eruditio : Indonesia Journal of Food and Drug Safety, 3(1), 29–37. https://doi.org/https://doi.org/10.54384/eruditio.v3i1.128
  12. Eysenbach, G. (2020). How to fight an infodemic: The four pillars of infodemic management. Journal of Medical Internet Research, 22(6). https://doi.org/10.2196/21820
  13. Haryalesmana, D. (2016). ID-Stopwords. https://github.com/masdevid/ID-Stopwords/blob/master/id.stopwords.02.01.2016.txt
  14. Hull, K., Kim, J. K., & Stilwell, M. (2019). Fotos de Béisbol: An Examination of the Spanish-language Instagram Accounts of Major League Baseball Teams. Howard Journal of Communications, 30(3), 249–264. https://doi.org/10.1080/10646175.2018.1471756
  15. Islam, M. S., Sarkar, T., Khan, S. H., Mostofa Kamal, A.-H., Hasan, S. M. M., Kabir, A., Yeasmin, D., Islam, M. A., Amin Chowdhury, K. I., Anwar, K. S., Chughtai, A. A., & Seale, H. (2020). COVID-19-Related Infodemic and Its Impact on Public Health: A Global Social Media Analysis. The American Journal of Tropical Medicine and Hygiene, 103(4), 1621–1629. https://doi.org/10.4269/ajtmh.20-0812
  16. Jarreau, P. B., Dahmen, N. S., & Jones, E. (2019). Instagram and the science museum: a missed opportunity for public engagement. Journal of Science Communication, 18(2), 1–22. https://doi.org/10.22323/2.18020206
  17. Karapanos, E., Teixeira, P., & Gouveia, R. (2016). Need fulfillment and experiences on social media: A case on Facebook and WhatsApp. Computers in Human Behavior, 55, 888–897. https://doi.org/https://doi.org/10.1016/j.chb.2015.10.015
  18. Kemp, S. (2021). Digital 2021 Indonesia. https://datareportal.com/reports/digital-2021-indonesia
  19. Khan, G. F. (2013). The Government 2.0 utilization model and implementation scenarios. Information Development. https://doi.org/10.1177/0266666913502061
  20. Khan, G. F. (2017). Social Media for Government. Springer Books.
  21. Koto, F., & Rahmaningtyas, G. Y. (2017). InSet Lexicon : Evaluation of a Word List for Indonesian Sentiment Analysis in Microblogs InSet Lexicon : Evaluation of a Word List for Indonesian Sentiment Analysis in Microblogs. International Conference on Asian Languange Processing (IALP). https://doi.org/10.1109/IALP.2017.8300625
  22. La, V.-P., Pham, T.-H., Ho, M.-T., Nguyen, M.-H., P. Nguyen, K.-L., Vuong, T.-T., Nguyen, H.-K. T., Tran, T., Khuc, Q., Ho, M.-T., & Vuong, Q.-H. (2020). Policy Response, Social Media and Science Journalism for the Sustainability of the Public Health System Amid the COVID-19 Outbreak: The Vietnam Lessons. In Sustainability (Vol. 12, Issue 7). https://doi.org/10.3390/su12072931
  23. Larsson, A. O. (2018). The News User on Social Media: A comparative study of interacting with media organizations on Facebook and Instagram. Journalism Studies, 19(15), 1–18. https://doi.org/10.1080/1461670X.2017.1332957
  24. Mergel, I. (2013). Social Media in the Public Sector: A Guide to Participation, Collaboration, and Transparency in the Networked World. Jossey-Bass.
  25. Naseem, U., Razzak, I., & Eklund, P. W. (2020). A survey of pre-processing techniques to improve short-text quality: a case study on hate speech detection on twitter. Multimedia Tools and Applications. https://doi.org/10.1007/s11042-020-10082-6
  26. Pennycook, G., McPhetres, J., Zhang, Y., Lu, J. G., & Rand, D. G. (2020). Fighting COVID-19 Misinformation on Social Media: Experimental Evidence for a Scalable Accuracy-Nudge Intervention. Psychological Science, 31(7), 770–780. https://doi.org/10.1177/0956797620939054
  27. Seleck, T. (2019). Emoji sentiment data. https://www.kaggle.com/thomasseleck/emoji-sentiment-data
  28. Silva, P. C. L., Batista, P. V. C., Lima, H. S., Alves, M. A., Guimarães, F. G., & Silva, R. C. P. (2020). COVID-ABS: An agent-based model of COVID-19 epidemic to simulate health and economic effects of social distancing interventions. Chaos, Solitons & Fractals, 139, 110088. https://doi.org/https://doi.org/10.1016/j.chaos.2020.110088
  29. Sohrabi, C., Alsafi, Z., O’Neill, N., Khan, M., Kerwan, A., Al-Jabir, A., Iosifidis, C., & Agha, R. (2020). World Health Organization declares global emergency: A review of the 2019 novel coronavirus (COVID-19). International Journal of Surgery, 76, 71–76. https://doi.org/https://doi.org/10.1016/j.ijsu.2020.02.034
  30. Tangcharoensathien, V., Calleja, N., Nguyen, T., Purnat, T., D’Agostino, M., Garcia-Saiso, S., Landry, M., Rashidian, A., Hamilton, C., AbdAllah, A., Ghiga, I., Hill, A., Hougendobler, D., van Andel, J., Nunn, M., Brooks, I., Sacco, P. L., de Domenico, M., Mai, P., … Briand, S. (2020). Framework for managing the COVID-19 infodemic: Methods and results of an online, crowdsourced who technical consultation. Journal of Medical Internet Research, 22(6), 1–8. https://doi.org/10.2196/19659
  31. Wu, Z., & McGoogan, J. M. (2020). Characteristics of and Important Lessons from the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72314 Cases from the Chinese Center for Disease Control and Prevention. JAMA - Journal of the American Medical Association, 323(13), 1239–1242. https://doi.org/10.1001/jama.2020.2648
  32. Yang, Y., Deng, W., Zhang, Y., & Mao, Z. (2021). Promoting public engagement during the covid-19 crisis: How effective is the wuhan local government’s information release? International Journal of Environmental Research and Public Health, 18(1), 1–17. https://doi.org/10.3390/ijerph18010118
  33. Zhang, S., Pian, W., Ma, F., Ni, Z., & Liu, Y. (2021). Characterizing the COVID-19 infodemic on chinese social media: Exploratory study. JMIR Public Health and Surveillance, 7(2). https://doi.org/10.2196/26090