Abstract
The Belt and Road Initiative (BRI) is an ambitious development project to build road and sea infrastructure through parts of Asia, Europe, and Africa that will encourage international trade and development. However, since its launch, a major concern and central research theme has been the possibility of the initiative being a ‘debt trap’ and an opportunity for China to gain power over countries like Indonesia. Previous research adopting more qualitative approaches have identified negative reactions to the BRI in terms of China’s intentions. However, there is a gap in the extant research focusing on the systematic evaluation of the BRI discourse on social media leveraging computational methodologies, particularly content and network analysis. Understanding the structure of the BRI discourse network can reveal key information actors that are driving the propagation of information through the network. As such, we extracted 12,985 tweets from Twitter to understand the different topics being discussed about the BRI in Indonesia. Latent Dirichlet Allocation (LDA) topic model algorithm classified the tweets into topic groups and helped us understand each topic’s underlying theme. In addition, the user and user’s follower data was analyzed to understand the information flow network and identify the most influential users within the network. While some users speculated on China’s good intentions for Indonesia, others argued that Indonesia acts like foreign minions controlled by the Chinese government. Furthermore, we identified key information actors within the network that are important and well-positioned for the diffusion of information across the network.
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Acknowledgements
This research is funded in part by the U.S. National Science Foundation (OIA-1946391, OIA-1920920, IIS-1636933, ACI-1429160, and IIS-1110868), U.S. Office of the Under Secretary of Defense for Research and Engineering (FA9550-22-1-0332), U.S. Office of Naval Research (N00014-10-1-0091, N00014-14-1-0489, N00014-15-P-1187, N00014-16-1-2016, N00014-16-1-2412, N00014-17-1-2675, N00014-17-1-2605, N68335-19-C-0359, N00014-19-1-2336, N68335-20-C-0540, N00014-21-1-2121, N00014-21-1-2765, N00014-22-1-2318), U.S. Air Force Research Laboratory, U.S. Army Research Office (W911NF-20-1-0262, W911NF-16-1-0189, W911NF-23-1-0011), U.S. Defense Advanced Research Projects Agency (W31P4Q-17-C-0059), Arkansas Research Alliance, the Jerry L. Maulden/Entergy Endowment at the University of Arkansas at Little Rock, and the Australian Department of Defense Strategic Policy Grants Program (SPGP) (award number: 2020-106-094). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the funding organizations. The researchers gratefully acknowledge the support.
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Nwana, L., Onyepunuka, U., Alassad, M., Agarwal, N. (2023). Computational Analysis of the Belt and Road Initiative (BRI) Discourse on Indonesian Twitter. In: Takada, H., Marutschke, D.M., Alvarez, C., Inoue, T., Hayashi, Y., Hernandez-Leo, D. (eds) Collaboration Technologies and Social Computing. CollabTech 2023. Lecture Notes in Computer Science, vol 14199. Springer, Cham. https://doi.org/10.1007/978-3-031-42141-9_14
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