Identifying and Eliminating Majority Illusion in Social Networks
Identifying and Eliminating Majority Illusion in Social Networks
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DOI：
10.1609/aaai.v37i4.25634
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发表时间：
2023-06
期刊：
影响因子：
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通讯作者：
Umberto Grandi;Lawqueen Kanesh;Grzegorz Lisowski;M. Ramanujan;P. Turrini
中科院分区：
文献类型：
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作者：
Umberto Grandi;Lawqueen Kanesh;Grzegorz Lisowski;M. Ramanujan;P. Turrini
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，这促使人们寻找算法来检测并在可能的情况下纠正这种不良现象。在本文中，我们发起了计算研究的多数错觉在社交网络，提供NP-硬度和参数化的复杂性结果，其发生和消除。
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.