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Ahad Zehmakan's talk on Why Misinformation Spread Fast in Social Networks, and How to Stop It

·259 words·2 mins

Time, Date, Location: 11:00, Friday, 16 February, 2024, Ian Ross Building Seminar Room

Title: Why Misinformation Spread Fast in Social Networks, and How to Stop It

Abstract: We discuss a misinformation spreading model where individuals are connected via a graph structure, representing a social network. Initially, only a small subset of the individuals are spreading a piece of misinformation. Each individual who is connected to a spreader starts spreading with some probability as a function of their trust in the spreader. We focus on determining the graph parameters which govern the magnitude and pace that the misinformation spreads in this model. We prove that for the misinformation to spread to a sizable fraction of the individuals, the network needs to enjoy “strong” expansion properties and most nodes should be in “well-connected” communities. Both of these characteristics are, arguably, present in real-world social networks up to a certain degree, shedding light on the driving force behind the extremely fast spread of misinformation in social networks. We, then, formulate a collection of countermeasures to stop the spread of misinformation. Our experiments on real-world graph data demonstrate that our novel decentralized countermeasures (which are executed by the individuals) outperform the previously studied centralized ones (which need to be imposed by a third entity, such as governments).

Bio: Ahad N. Zehmakan is a faculty member in the School of Computing at The Australian National University and received his PhD from ETH Zurich in 2020. His research mostly focuses on social network analysis using various algorithmic, graph theory, combinatorial optimization, and data mining techniques.