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<https://discovery.ucl.ac.uk/id/eprint/10205241> <http://purl.org/dc/terms/title> "Agent-based Models of Social Learning in Opinion Dynamics"^^<http://www.w3.org/2001/XMLSchema#string> .
<https://discovery.ucl.ac.uk/id/eprint/10205241> <http://purl.org/ontology/bibo/abstract> "With phenomena such as the rise of fake news and the spread of online misinformation, the need to develop a quantitative understanding of opinion dynamics in online social networks (OSNs) has become evident. By gauging agent-based models\r\n(ABMs), this thesis aims to better understand the relationship which exists between\r\nmis/dis-information spread and opinion formation, in the interest of determining the\r\neffectiveness of current counter-strategies and ultimately striving towards improved\r\nones.\r\nA social learning procedure of distributed hypothesis testing (DHT) is invoked\r\nin order to build a framework where there exists a notion of ground-truth. Agents\r\naim to learn this ground-truth among a set of competing hypotheses utilizing this\r\nprocedure of DHT. A sub-population of agents, referred to as conspirators which\r\npromote a fixed non-truth, are introduced where the dynamics are observed given\r\na level of the network being perturbed. To understand such effects, a metric of\r\ntruthfulness is developed, which describes the network’s collective belief in the\r\nground-truth.\r\nA feature of the DHT procedure invoked is the distinction between what an\r\nagent publicly expresses and privately believes. This distinction gives rise to a\r\nmeans of measuring an agent’s cognitive dissonance, evocative of the mental toll\r\nwhich may arise when a decision is faced within an environment of potentially\r\nconflicting information.\r\nA main prong of this thesis is to understand whether the effects of misinformation may be mitigated. Given our DHT framework, it is explored whether there\r\nare beneficial effects of the injection of noise, which has been shown to have stabilizing effects in complex system contexts. Finally, we investigate by whom or\r\nwhat the moderation of misinformation should derive. We classify current counterstrategies (debunking, prebunking, deplatforming, and inoculation) as centralized\r\nand/or decentralized and simulate such correcting interventions"^^<http://www.w3.org/2001/XMLSchema#string> .
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