Identifying and Eliminating Majority Illusion in Social Networks

Umberto Grandi, Lawqueen Kanesh, Grzegorz Lisowski, M. Ramanujan, P. Turrini
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Abstract

Majority illusion occurs in a social network when the majority of the network vertices belong to a certain type but the majority of each vertex's neighbours belong to a different type, therefore creating the wrong perception, i.e., the illusion, that the majority type is different from the actual one. From a system engineering point of view, this motivates the search for algorithms to detect and, where possible, correct this undesirable phenomenon. In this paper we initiate the computational study of majority illusion in social networks, providing NP-hardness and parametrised complexity results for its occurrence and elimination.
识别和消除社交网络中的多数错觉
多数错觉发生在社交网络中,当大多数网络顶点属于某种类型,但每个顶点的大多数邻居属于不同类型时,因此产生错误的感知,即错觉,即大多数类型与实际类型不同。从系统工程的角度来看,这激发了对算法的搜索,以检测并在可能的情况下纠正这种不良现象。本文对社会网络中的多数错觉进行了计算研究,给出了多数错觉发生和消除的np -硬度和参数化复杂度结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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