Hidden messages: mapping nations’ media campaigns
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10588_2023_Article_9382.pdf
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3.62 MB
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Author(s)
Erhardt, Keeley
Pentland, Alex
Date Issued
August 29, 2023
Publisher
Springer US
Citation
Erhardt, Keeley and Pentland, Alex. 2023. "Hidden messages: mapping nations’ media campaigns."
Version
Final published version
Abstract
Abstract
Powerful actors have engaged in information control for centuries, restricting, promoting, or influencing the information environment as it suits their evolving agendas. In the Digital Age, information control has moved online, and information operations now target the online platforms that play a critical role in news engagement and civic debate. In this paper, we use a discrete-time stochastic model to analyze coordinated activity in an online social network, representing the behaviors of accounts as interacting Markov chains. From a dataset of 31,521 tweets posted by 206 accounts, half of which were identified by Twitter as participating in a state-linked information operation, we evaluate the coordination, measured by the apparent influence, between pairs of state-linked accounts compared to unaffiliated accounts. Our analysis reveals that state-linked actors demonstrate significantly higher levels of coordination among themselves compared to their coordination with unaffiliated accounts. Furthermore, the degree of coordination observed between state-linked accounts is more than seven times greater than the coordination observed between unaffiliated accounts. Moreover, we find that the account that represented the most coordinated activity in the network had no followers, demonstrating the power of our modeling approach to unearth hidden connections even in the absence of explicit network structure.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
MIT Connection Science (Research institute)
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Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.1007/s10588-023-09382-7
