Email this article 
Analysing the Twitter social media network in voicing opinions on money loundering issue in Indonesia
Abstract
This study aims to examine the Twitter social media network concerning the money laundering issue involving the Indonesian Ministry of Finance. The primary goal is identifying and highlighting the individuals or entities significantly influencing online discussions. Further, the study looks at the intricacies of public perception and communication about this pressing issue within the Ministry. The study gathered and analyzed Twitter data using social network analysis methodologies, consisting of 6742 nodes and 744 edges. The findings demonstrate ten actors exhibit the most prominent clusters, whereas five exhibit the maximum links. The significance of the Twitter user was @seeksixsuck, who highlights the importance of religious people in ongoing conversations. This research study enhances the social media environment's comprehension of money laundering within the Ministry of Finance, providing insights into the interconnected relationships and individuals influencing the ongoing conversation. The study's findings provide significant value in facilitating public engagement initiatives and promoting a more knowledgeable and engaged population in the ongoing battle against money laundering.
Keywords
Full Text:
PDFReferences
Aditiawarman, U., Lumbia, M., Mantoro, T., & Ibrahim, A. A. (2023). Social network analysis: identification of communication and information dissemination (case study of holywings). Jurnal Online Informatika, 8(1), 19-26. https://doi.org/10.15575/join.v8i1.911
Adniati, S., Irwansyah, I., & Awanis, Z. Y. (2023). Social network analysis of Twitter users on BTS topic using degree centrality, betweenness centrality, and closeness centrality. InPrime: Indonesian Journal of Pure and Applied Mathematics, 5(2), 123-135. https://doi.org/10.15408/inprime.v5i2.28722
Alfarizy, S. N., & Arianto, I. D. (2024). Analisis jaringan komunikasi isu adakami pada platfrom media sosial Twitter (X). JIIP-Jurnal Ilmiah Ilmu Pendidikan, 7(7), 6437-6446. https://doi.org/10.54371/jiip.v7i7.4622
Alfarizy, S. N., & Arianto, I. D. (2024). Analisis jaringan komunikasi isu Adakami pada platfrom media sosial Twitter (X). JIIP-Jurnal Ilmiah Ilmu Pendidikan, 7(7), 6437-6446. https://doi.org/10.54371/jiip.v7i7.4622
Alhassan, A. Y. (2024). Social capital and information flow in decision making: a social network analysis of actors in a road expansion project in Kristiansand, Norway. International Journal of Politics, Culture, and Society. https://doi.org/10.1007/s10767-024-09488-z
Amalia, F. P., & Abadi, T. W. (2024). Social media network analysis corruption Harvey Moies on Twitter: Analisis jaringan media sosial korupsi Harvey Moies di Twitter. Jurnal Ilmu Sosial, Manajemen, Akuntansi Dan Bisnis, 5(3), 346 - 360. https://doi.org/10.47747/jismab.v5i3.1863
BBCNewsIndonesia. (2023, March 11). Sri Mulyani: Ada 964 pegawai Kemenkeu diduga memiliki harta tidak wajar dan 16 kasus dilimpahkan ke hukum. BBC News Indonesia. https://www.bbc.com/indonesia/articles/cw0eykk6dnro
Bhowmik, K., & Ralescu, A. (2020, October). Taking a close look at Twitter communities and clusters. In International Conference on Modelling and Development of Intelligent Systems (pp. 187-201). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-68527-0_12
Butts, C. T. (2020). A dynamic process reference model for sparse networks with reciprocity. Journal of Mathematical Sociology, 46(1), 1–27. https://doi.org/10.1080/0022250X.2020.1795652
Diepenmaat, F. (2021). (The fight against) money laundering: It’s all about networks. Corruption Networks: Concepts and Applications, 115-130. https://doi.org/10.1007/978-3-030-81484-7_7
Gaisbauer, F., Pournaki, A., Banisch, S., & Olbrich, E (2009). How Twitter affects the perception of public opinion: Two case studies. arXiv preprint arXiv. https://doi.org/10.13140/RG.2.2.32140.95363
Gardasevic, S., Jaiswal, A., Lamba, M., Funakoshi, J., Chu, K. H., Shah, A., ... & Washington, P. (2024). Public health using social network analysis during the COVID-19 era: A systematic review. Information, 15(11), 690. Information. https://doi.org/10.3390/info15110690
Gong, X., Yu, H., & Yu, T. (2023). Literature review on the influence of social networks. In SHS Web of Conferences (Vol. 153, p. 01009). EDP Sciences. https://doi.org/10.1051/shsconf/202315301009
Gunawan, A. I., Monoarfa, H., Hendrayati, H., Rahayu, A., Bahri, K. N., & Huda, M. (2023). Social media user perception on communication types: Comparing one-two way of communicating brand. Journal of Marketing, 3(1), 50-64. https://doi.org/10.35313/jmi.v3i1.59
Hampton, K. N., Shin, I., & Lu, W. (2017). Social media and political discussion: when online presence silences offline conversation. Information, Communication & Society, 20(7), 1090-1107. https://doi.org/10.1080/1369118X.2016.1218526
Han, R. (2023). More talk, more support? The effects of social network interaction and social network evaluation on social support via social media. Psychology Research and Behavior Management, 3857-3866. https://doi.org/10.2147/prbm.s424443
Imanpour, M. (2017). The role of social networks for combating money laundering.
Judina, D. I., & Riazantseva, A. V. (2024). Analysis of public discussions in social media as a method for studying social issues. Galactica Media: Journal of Media Studies, 6(1), 100-123. https://doi.org/10.46539/gmd.v6i1.442
KhosraviNik, M. (Ed.). (2023). Social media and society: Integrating the digital with the social in digital discourse (Vol. 100). John Benjamins Publishing Company.
Kim, Y., Kim, B., Hwang, H. S., & Lee, D. (2020). Social media and life satisfaction among college students: A moderated mediation model of SNS communication network heterogeneity and social self-efficacy on satisfaction with campus life. The Social science journal, 57(1), 85-100. https://doi.org/10.1016/j.soscij.2018.12.001
Krzyżanowski, M., & Tucker, J. A. (2018). Re/constructing politics through social & online media: Discourses, ideologies, and mediated political practices. Journal of Language and Politics, 17(2), 141-154. https://doi.org/10.1075/JLP.18007.KRZ
Lin, Y. (2022). Social media for collaborative planning: A typology of support functions and challenges. Cities, 125, 103641. https://doi.org/10.1016/j.cities.2022.103641
Lina, L. F., Hartini, S., Mardhiyah, D., Saifuddin, M., Mutiarasari, N. A. G., & Novita, D. (2024). Understanding opinion leadership in social media: the role of perceived fit with personal interests in purchase behavior and social media engagement. International Journal of Economics and Management/International Journal of Economics and Management, 18(3), 343–357. https://doi.org/10.47836/ijeam.18.3.04
Logan, A. P., LaCasse, P. M., & Lunday, B. J. (2023). Social network analysis of Twitter interactions: a directed multilayer network approach. Social Network Analysis and Mining, 13(1), 65. https://doi.org/10.1007/s13278-023-01063-2
Namugera, F., Wesonga, R., & Jehopio, P. (2019). Text mining and determinants of sentiments: Twitter social media usage by traditional media houses in Uganda. Computational Social Networks, 6, 1-21. https://doi.org/10.1186/s40649-019-0063-4
Permana, F. C., Wicaksono, Z. M., Kurniawan, C., Abdullah, A. S., & Ruchjana, B. N. (2021). Perception analysis of the Indonesian society on twitter social media on the increase in BPJS kesehatan contribution in the Covid 19 pandemic era. In Journal of Physics: Conference Series (Vol. 1722, No. 1, p. 012022). IOP Publishing. https://doi.org/10.1088/1742-6596/1722/1/012022
Prayudi, Fatonah, S., & Shafira, J. (2021). Covid-19 on online news media: A discourse analysis of indonesian government crisis management on Kompas.com. Jurnal Komunikasi: Malaysian Journal of Communication, 37(3), 38–53. https://doi.org/10.17576/JKMJC-2021-3703-03
Prayudi, Susilo, M. E., & Florestiyanto, M. Y. (2023). Sentiment analysis of public comments on government policies in handling COVID-19: The case of Indonesia. Baltic Journal of Law & Politics, 16(1), Article 1.
Rachman, A. (2023). Misteri uang Rp300 T di Kemenkeu terbongkar, siapa sumbernya? CNBC Indonesia. https://www.cnbcindonesia.com/news/20230316053450-4-422042/misteri-uang-rp300-t-di-kemenkeu-terbongkar-siapa-sumbernya
Rathore, A. K., Kar, A. K., & Ilavarasan, P. V. (2017). Social media analytics: Literature review and directions for future research. Decision Analysis, 14(4), 229-249. https://doi.org/10.1287/DECA.2017.0355
Rutechura, F. (2018). The Discourse of conflict in social media networks. Utafiti, 13(1), 93-102. https://doi.org/10.1163/26836408-01301007
Santosa, B. D., Fatimah, N., Kusumaningtyas, N. I., & Aesyi, U. S. (2023). Analisa jaringan dan pola penyedia layanan judi online di Twitter menggunakan social network analysis. Angkasa: Jurnal Ilmiah Bidang Teknologi, 15(2), 169-176. https://doi.org/10.28989/angkasa.v15i2.1778
Santoso, A. D., Rinjany, D., & Bafadhal, O. M. (2020). Social media and local government in indonesia: adoption, use and stakeholder engagement. Romanian Journal of Communication and Public Relations, 22(3), 21–35. https://doi.org/10.21018/rjcpr.2020.3.307
Sari, D. N., & Kurniati, K. (2022). Penerapan algoritma Katz pada struktur komunitas jejaring sosial Twitter. Jurnal Bina Komputer, 4(2), 7-14. https://doi.org/10.33557/jbkom.v4i2.2196
Sari, E. A., Setiawan, R. A. D., & Jandevi, U. (2023). Social media in electoral communication: A case study of strategic initiatives by Bantul Election Commission for the 2024 elections. CHANNEL: Jurnal Komunikasi, 11(2), 137-143. https://doi.org/10.12928/channel.v11i2.377
Sinaga, N., Hasan, K., Nacia, M., Aklima, R., & Jannah, M. (2024, January). Analysis of political communication on the role of social media towards the 2024 general election. In Proceedings of International Conference on Social Science, Political Science, and Humanities (ICoSPOLHUM (Vol. 4, pp. 00039-00039). https://doi.org/10.29103/icospolhum.v4i.468
Smith, M. A. (2013, May). NodeXL: Simple network analysis for social media. In 2013 international conference on collaboration technologies and systems (CTS) (pp. 89-93). IEEE.
Sueki, M. (2022). Network of investment-oriented social media. In Digital designs for money, markets, and social dilemmas (pp. 405-425). Springer Nature Singapore. https://doi.org/10.1007/978-981-19-0937-5_18
Urse, E., & Tasențe, T. (2022). The role of social media in the development of the communication strategy of public institutions. Ars aequi, 12, 280-288. https://doi.org/10.47577/10.1234/arsaequi.12.1.232
Utami, S. R., Safitri, R. N., & Kuncoroyakti, Y. A. (2021). Network analysis and actors #CancelOmnibusLaw on Twitter social media using Social Network Analysis (SNA). JCommsci-Journal Of Media and Communication Science, 4(3), 135-148. https://doi.org/10.29303/jcommsci.v4i3.111
Wang, L., Niu, J., & Yu, S. (2019). SentiDiff: Combining textual information and sentiment diffusion patterns for Twitter sentiment analysis. IEEE Transactions on Knowledge and Data Engineering, 32(10), 2026-2039. https://opus.lib.uts.edu.au/handle/10453/147966
Wijayanto, G., Jushermi, J., Nursanti, A., Pramadewi, A., Novandalina, A., & Rivai, Y. (2024). Influence of dynamic capability, market research, and social capital on marketing sustainability and competitiveness of tourism creative economy in Indonesia. International Journal of Business, Law, and Education, 5(1), 1046-1063. https://doi.org/10.56442/ijble.v5i1.500
Yu, X., Yuan, C., Kim, J., & Wang, S. (2021). A new form of brand experience in online social networks: An empirical analysis. Journal of Business Research, 130, 426-435. https://www.sciencedirect.com/science/article/abs/pii/S0148296320301053
Zulkarnain, M. F., Hilalludin, H., & Suny, F. S. A. (2024). Relevansi pengampunan korupsi dalam perspektif Islam dengan hukum yang berlaku. ALADALAH: Jurnal Politik, Sosial, Hukum dan Humaniora, 2(4), 139-147. https://doi.org/10.59246/aladalah.v2i4.957
DOI: http://dx.doi.org/10.24329/aspikom.v9i1.1392
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License