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Mis- and Disinformation in a Bounded Confidence Model
Artificial Intelligence ( IF 14.4 ) Pub Date : 2021-02-01 , DOI: 10.1016/j.artint.2020.103415
Igor Douven , Rainer Hegselmann

Abstract The bounded confidence model has been widely used to formally study groups of agents who are sharing opinions with those in their epistemic neighborhood. We revisit the model with an eye toward studying mis- and disinformation campaigns, which have been much in the news of late. To that end, we introduce typed agents into the model, specifically agents who can be irresponsible in different ways, most notably, by being deceitful, but also by being reluctant to try and obtain information from the world directly. We further add a mechanism of confidence dynamics to the model, which—among other things—allows agents to adapt the closeness threshold for counting others as being their epistemic neighbors. This will be used to study the effectiveness of possible defense mechanisms against mis- and disinformation efforts.

中文翻译:

有界置信模型中的错误和虚假信息

摘要 有界置信模型已被广泛用于正式研究与其认知邻域内的人分享意见的代理组。我们重新审视这个模型,着眼于研究错误和虚假宣传活动,这些活动最近成为新闻。为此,我们在模型中引入了类型化代理,特别是那些可能以不同方式不负责任的代理,最显着的是,通过欺骗,但也不愿意尝试直接从世界获取信息。我们进一步向模型添加了置信动态机制,除其他外,该机制允许代理调整接近度阈值,以将其他人视为他们的认知邻居。这将用于研究针对错误和虚假信息努力的可能防御机制的有效性。
更新日期:2021-02-01
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