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Internet shutdown as a theoretical problem of political science, or what we do (not) understand about network protest mobilization

Akhremenko A.S.,

HSE University, Moscow, Russia, aakhremenko@hse.ru

elibrary_id: 124097 | ORCID: 0000-0001-8002-7307 | RESEARCHER_ID: L-3000-2015

Article received: 2023.10.29. Accepted: 2023.12.29


DOI: 10.17976/jpps/2024.02.09
EDN: CJZFRF

Rubric: Theory and methodology of political studies

For citation:

Akhremenko A.S. Internet shutdown as a theoretical problem of political science, or what we do (not) understand about network protest mobilization. – Polis. Political Studies. 2024. No. 2. https://doi.org/10.17976/jpps/2024.02.09. EDN: CJZFRF

This research is supported by the Russian Science Foundation under grant no. 20-18-00274, https:// rscf.ru/en/project/20-18-00274/, HSE University. The author is grateful to his PhD student, Sergey Zheglov, for his valuable assistance in implementing the computational experiment in the Python environment.

Abstract

The influence of Internet communication on “street” protest activity is the focus of this paper. In recent years, there has been some stagnation in this area of research: a shortage of breakthroughs that would indicate new research directions or at least significantly strengthen the empirical foundation of the already established hypotheses. The paradox is that when considering the impact of the global network on political behavior, the network aspect itself, reflecting the structural characteristics of information exchange, remains on the far periphery of the research field. In this work, we try to partially fill this gap by proposing a set of concepts that, on the one hand, are “rooted” in network analysis, and on the other, reflect the important properties of the interaction of individuals within the framework of online and offline political mobilization. The simultaneous focus on the configuration of networks and the dynamics of participation also determines the approach to building such a theory - formal modeling. A key feature of the model's design is the identification of two structures in the overall communication system: core (strong offline ties) and augmented (core network plus online connections). The constructed model made it possible to strictly define the key concept - the network mobilization capacity, and to test the hypotheses built on its basis. Computational experiments show that the ratio of mobilization capacities of core and augmented networks is a strong predictor of the effect of Internet shutdown. Although specific features of the structure and dynamics of networks, such as the activation of “broker” nodes, are of great importance, the paper also discusses the prospects for empirical operationalization of the concepts proposed by the author. 

Keywords

political mobilization, political coordination, formal model, agent-based model, Internet shutdown, social media, political protest.

 Full Text

Acemoglu, D., Hassan, T., & Tahoun, A. (2018). The power of the street: evidence from Egypt's Arab Spring. The Review of Financial Studies, 31(1), 1-42. https://doi.org/10.1093/rfs/hhx086

Amorim, G., Lima, R., & Sampaio, B. (2022). Broadband Internet and protests: evidence from the Occupy movement. Information Economics and Policy, 60, 100982. https://doi.org/10.1016/j.infoecopol.2022.100982.

Anderson, A. (2021). “Networked” revolutions? ICTs and protest mobilization in non-democratic regimes. Political Research Quarterly, 74(4), 1037-1051. https://doi.org/10.1177/1065912920958071

Clarke, K., & Kocak, K. (2020). Launching revolution: social media and the Egyptian uprising's first movers. British Journal of Political Science, 50, 1024-1045. https://doi.org/10.1017/S 0007123418000194.

Enikolopov, R., Makarin, A., & Petrova, M. (2020). Social media and protest participation: evidence from Russia. Econometrica, 88(4), 1479-1514. https://doi.org/10.3982/ECTA14281

Erdos, P., & Rdnyi, A. (1959). On random graphs. Publicationes Mathematicae, 6, 290-297.

Fergusson, L., & Molina, C. (2019). Facebook causes protests. Documento CEDE, 41. https://doi.org/10.2139/ssrn.3553514

Gonzdlez, F. (2020). Collective action in networks: evidence from the Chilean student movement. Journal of Public Economics, 188, 104220. https://doi.org/10.1016/j.jpubeco.2020.104220

Gonzalez-Baildn, S., & Wang N. (2016). Networked discontent: the anatomy of protest campaigns in social media. Social Networks, 44, 95-104. https://doi.org/10.1016/j.socnet.2015.07.003

Granovetter, M. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360-1380. https://doi.org/10.1086/225469

Granovetter, M. (1978). Threshold models of collective behavior. The American Journal of Sociology, 83(6), 1420-1443. https://doi.org/10.1086/226707

Hassanpour, N. (2017). Leading from the periphery and network collective action. Cambridge: Cambridge University Press.

Himelboim, I., Smith, M.A., Rainie, L., Shneiderman, B., & Espina, C. (2017). Classifying Twitter topic-networks using social network analysis. Social Media + Society, 3(1), 1-13. https://doi.org/10.1177/2056305117691545

Jones, J.J., Settle, J., Bond, R., Fariss, Ch., Marlow, C., & Fowler, J. (2013). Inferring tie strength from online directed behavior. PloS One, 8(1), e52168. https://doi.org/10.1371/journal.pone.0052168

Little, A. (2016). Communication technology and protest. Journal of Politics, 78(1), 152-166. https://doi.org/10.1086/683187

Olson M. (1965). The logic of collective action. Cambridge: Harvard University Press.

Petrov, A., Akhremenko, A., & Zheglov, S. (2023). Dual Identity in repressive contexts: an agent- based model of protest dynamics. Social Science Computer Review, 41(6), 2249-2273. https://doi.org/10.1177/08944393231159953

Rydzak, J., Karanja, M., & Opiyo, N. (2020). Internet shutdowns in Africa: dissent does not die in darkness: network shutdowns and collective action in African Countries. International Journal of Communication, 14, 4264-4287. https://ijoc.org/index.php/ijoc/article/view/12770/3185

Siegel, D. (2009). Social networks and collective action. American Journal of Political Science, 53(1), 122-138. https://doi.org/10.1111/j.1540-5907.2008.00361.x

Steinert-Threlkeld, Z. (2017). Spontaneous collective action: peripheral mobilization during the Arab Spring. American Political Science Review, 111(2), 379-403. https://doi.org/10.1017/S0003055416000769

Steinert-Threlkeld, Z., Mocanu, D., Vespignani, A., & Fowler, J. (2015). Online social networks and offline protest. EPJ Data Science, 4(19). https://doi.org/10.1140/epjds/s13688-015-0056-y

Watts, D., & Strogatz, S. (1998). Collective dynamics of ‘small-world' networks. Nature, 393, 440-442. https://doi.org/10.1038/30918

Wooldridge, J.M. (2010). Econometric analysis of cross section and panel data. Cambridge: MIT Press.

Zhuravskaya, E., Petrova, M., & Enikolopov, R. (2020). Political effects of the Internet and social media. Annual Review of Economics, 12, 415-438. https://doi.org/10.1146/annurev-economics-081919-050239

Akhremenko, A.S., Stukal, D.K., & Petrov, A.P. (2020). Network vs message in protest diffusion on social media: theoretical and data analytics perspectives. Polis. Political Studies, 2, 73-91. (In Russ.) https://doi.org/10.17976/jpps/2020.02.06

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