Abstract
Two massive earthquakes struck Kahramanmaraş district of Türkiye on 6 February 2023, leaving loss of life and damage in a catastrophic scale. Many blamed the government for its inefficiency in dealing with the disaster. #devletyok (there is no government) was a hashtag used in the aftermath in social networking sites. We analyze the retweet network around the hashtag on 24th February, two weeks after the disaster, and aim to extract topological characteristics of the network, the influential spreaders in the network and the source of the diffusion. We make use of centrality measures, the HITS algorithm, PageRank algorithm and the k-shell decomposition in order to detect the influential spreaders. The social network analysis here is different from much of the previous research in that we explore the central roles in an information diffusion on a network, where all nodes are active, representing an already diffused information. In-degree centrality, betweenness centrality and HITS algorithm provide useful results in detecting spreaders in our network, while closeness centrality, PageRank and k-shell decomposition supply no additional knowledge. We figure out three nodes in the network with central roles in the diffusion, one being the source node. Checking the account of this source node reveals an anonymous user, who does not declare his/her identity. The study here has useful future implications for political and governmental studies. Moreover, the procedure applied to detect influential spreaders has many potential use cases in other fields such as marketing and sociology.
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Adak, Z., Çetinkaya, A. (2024). Exploring Spreaders in a Retweet Network: A Case from the 2023 Kahramanmaraş Earthquake Sequence. In: García Márquez, F.P., Jamil, A., Hameed, A.A., Segovia Ramírez, I. (eds) Emerging Trends and Applications in Artificial Intelligence. ICETAI 2023. Lecture Notes in Networks and Systems, vol 960. Springer, Cham. https://doi.org/10.1007/978-3-031-56728-5_40
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