COVID-19 research spread in Indonesia on social media

  • La Tarifu Department of Communication, Halu Oleo University
  • Joko Joko Department of Communication, Halu Oleo University
  • Cecep Ibrahim Department of Library and Information Science, Halu Oleo University
  • Rahmat Fadhli Department of Educational Management, Faculty of Education, Yogyakarta State University
  • Sri Hartinah Research Center for Development of Science and Technology, Indonesian Institutes of Sciences
Keywords: COVID19, social media, research productivity, scientometric, altmetrics


Introduction. The purpose of this study is to determine the impact of Indonesian COVID-19 research. One of them is productive author, productive citations, the most popular social media to disseminate research results, the most popular articles on social media, mapping or distribution of research results visualization, and the correlation of social media data with citations.

Data Collection Method. The research data was taken from the Scopus database and this research use method Bibliometric, Altmetric, Scientometric, and linear regression tests.

Data Analysis. The data of the study was analyzed using program (, VOSViewer and SPSS software.

Result and Discussion. Pranata, R. was the productive author in producing Indonesian COVID-19 research. The University of Indonesia is the most productive institution. The study "Clinical, laboratory, and imaging features of COVID-19: A systematic review and meta-analysis" received the most citations and shares on social media. Mendeley is the most popular social media platform for disseminating research.

Conclusion. Based on the above findings, the spread of COVID-19 research in Indonesia on the most popular social media is mendeley 17.701, followed by Twitter 2.971 and news mentions 177. According to linear regression tests, mendeley is social media platform with a high correlation value of 0.814.


Abramo, G., & D’Angelo, C. A. (2014). How do you define and measure research productivity? Scientometrics, 101(2), 1129–1144.

Aljohani, N. R., Fayoumi, A., & Hassan, S. U. (2020). Bot prediction on social networks of Twitter in altmetrics using deep graph convolutional networks. Soft Computing, 24(15), 11109–11120.

Allahbadia, G. N. (2014). Thinking beyond the Thomson Reuters “impact factor.” Journal of Obstetrics and Gynecology of India, 64(4), 231–233.

Borgatti, S. P. (2012). Social network analysis, two-mode concepts in. In Computational Complexity (pp. 2912–2924). Springer New York.

Bornmann, L. (2014). Do altmetrics point to the broader impact of research ? An overview of benefits and disadvantages of altmetrics. Journal of Informetrics, 8(4), 895–903.

Bornmann, L., & Haunschild, R. (2016). To what extent does the Leiden manifesto also apply to altmetrics? A discussion of the manifesto against the background of research into altmetrics. Online Information Review, 40(4), 529–543.

Butler, J. S., Kaye, I. D., Sebastian, A. S., Wagner, S. C., Morrissey, P. B., Schroeder, G. D., Kepler, C. K., & Vaccaro, A. R. (2017). The evolution of current research impact metrics. Clinical Spine Surgery, 30(5), 226–228.

Chamberlain, S. (2013). Consuming article-level metrics: Observations and lessons. Information Standards Quarterly, 25(2), 4-13.

Cho, J. (2017). A comparative study of the impact of Korean research articles in four academic fields using altmetrics. Performance Measurement and Metrics, 18(1), 38–51.

Ellegaard, O., & Wallin, J. A. (2015). The bibliometric analysis of scholarly production: How great is the impact? Scientometrics, 105(3), 1809–1831.

Ezema, I. J., & Ugwu, C. I. (2019). Correlating research impact of library and information science journals using citation counts and altmetrics attention. Information Discovery and Delivery, 47(3), 143–153.

González-Alcaide, G., Salinas, A., & Ramos, J. M. (2018). Scientometrics analysis of research activity and collaboration patterns in Chagas cardiomyopathy. PLoS Neglected Tropical Diseases, 12(6), 1–22.

Haunschild, R., Bornmann, L., & Marx, W. (2016). Climate change research in view of bibliometrics. PLoS ONE, 11(7), 1–20.

Haustein, S., Peters, I., Bar-Ilan, J., Priem, J., Shema, H., & Terliesner, J. (2013). Coverage and adoption of altmetrics sources in the bibliometric community. Proceedings of ISSI 2013 - 14th International Society of Scientometrics and Informetrics Conference, 1, 468–483.

Ibrahim, C., Sitanggang, I. S., & Sukoco, H. (2019). Pengaruh media sosial terhadap sitasi publikasi internasional karya ilmiah Indonesia bidang pertanian dengan pendekatan altmetrics. BACA: Jurnal Dokumentasi dan Informasi, 40(1), 73-81.

Lamba, M., Kashyap, N., & Madhusudhan, M. (2021). Research evaluation of computer science publications using Altmetrics: a cohort study of Indian Central Universities. Global Knowledge, Memory and Communication, 70(4/5), 459–486.

Mingers, J., & Leydesdorff, L. (2015). A review of theory and practice in scientometrics. European Journal of Operational Research, 246(1), 1–19.

Ngadi, N., Meliana, R., & Purba, Y. A. (2020). Dampak pandemi COVID-19 terhadap PHK dan pendapatan pekerja di Indonesia. Jurnal Kependudukan Indonesia, 15(1), 43-48.

Nugroho, A. E. (2020). Survey on the impact of the COVID-19 pandemic on Indonesian Household Economy | Indonesian Institute of Sciences

Onyancha, O. B. (2017). Altmetrics of South African Journals: Implications for scholarly impact of South African Research. Publishing Research Quarterly, 33(1), 71–91.

Ouchi, A., Saberi, M. K., Ansari, N., Hashempour, L., & Isfandyari-Moghaddam, A. (2019). Do altmetrics correlate with citations? A study based on the 1,000 most-cited articles. Information Discovery and Delivery, 47(4), 192–202.

Pham, T., & Nugroho, A. (2022). Tourism-induced poverty impacts of COVID-19 in Indonesia. Annals of Tourism Research Empirical Insights, 3(2), 1-12.

Shrivastava, R., & Mahajan, P. (2016). Relationship between citation counts and Mendeley readership metrics: A case of top 100 cited papers in Physics Rishabh. New Library World, 117(3/4), 229–238.

Talmale, M. S., & Singh, S. N. (2015). Web-based information resources on scientometrics: A study. International Journal of Information Dissemination and Technology, 5(4), 244–253.

Tang, Y., Tseng, H., & Vann, C. (2020). Unwrap citation count, altmetric attention score and mendeley readership status of highly cited articles in the top-tier LIS journals. Global Knowledge, Memory and Communication, 69(8–9), 653–664.

Tella, A., & Olabooye, A. A. (2014). Bibliometric analysis of African Journal of Library, Archives and Information Science from 2000-2012. Library Review, 63(4/5), 305–323.

Uluyol, B., Secinaro, S., Calandra, D., & Lanzalonga, F. (2021). Mapping waqf research: A thirty-year bibliometric analysis. Journal of Islamic Accounting and Business Research, 12(5), 748–767.

Waltman, L., Calero-Medina, C., Kosten, J., Noyons, E. C. M., Tijssen, R. J. W., Van Eck, N. J., Van Leeuwen, T. N., Van Raan, A. F. J., Visser, M. S., & Wouters, P. (2012). The Leiden ranking 2011/2012: Data collection, indicators, and interpretation. Journal of the American Society for Information Science and Technology, 63(12), 2419–2432.

How to Cite
Tarifu, L., Joko, J., Ibrahim, C., Fadhli, R., & Hartinah, S. (2022). COVID-19 research spread in Indonesia on social media. Berkala Ilmu Perpustakaan Dan Informasi, 18(2), 247-258.