Eliminating Majority Illusion Is Easy

Majority illusion is a phenomenon in social networks wherein the decision by the majority of the network is not the same as one's personal social circle's majority, leading to an incorrect perception of the majority in a large network. We present polynomial-time algorithms which completely eliminate majority illusion by altering as few connections in the network as possible. Eliminating majority illusion ensures each neighbourhood in the network has at least a 1/2-fraction of the majority winner. This result is surprising as partially eliminating majority illusion is NP-hard. We generalize the majority illusion problem to an arbitrary fraction p and show that the problem of ensuring all neighbourhoods in the network contain at least a p-fraction of nodes consistent with a given preference is NP-hard, for nearly all values of p.

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Publication Details

Journal
Proceedings of the AAAI Conference on Artificial Intelligence
Published
2025-04-11
DOI
https://doi.org/10.1609/aaai.v39i13.33504
Primary Topic
Constraint Satisfaction and Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Eliminating Majority Illusion Is Easy

Max Dupré la Tour, Adrian Vetta, April Niu, Jack Dippel et al.
Proceedings of the AAAI Conference on Artificial Intelligence
Constraint Satisfaction and Optimization
article

Eliminating Majority Illusion Is Easy

Max Dupré la Tour, Adrian Vetta, April Niu, Jack Dippel, Sanjukta Roy
article en

Abstract

Majority illusion is a phenomenon in social networks wherein the decision by the majority of the network is not the same as one's personal social circle's majority, leading to an incorrect perception of the majority in a large network. We present polynomial-time algorithms which completely eliminate majority illusion by altering as few connections in the network as possible. Eliminating majority illusion ensures each neighbourhood in the network has at least a 1/2-fraction of the majority winner. This result is surprising as partially eliminating majority illusion is NP-hard. We generalize the majority illusion problem to an arbitrary fraction p and show that the problem of ensuring all neighbourhoods in the network contain at least a p-fraction of nodes consistent with a given preference is NP-hard, for nearly all values of p.

Proceedings of the AAAI Conference on Artificial IntelligenceVol. 39(13)
McGill University (CA), Indian Statistical Institute (IN)
Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 76%
Constraint Satisfaction and Optimization
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Eliminating Majority Illusion Is Easy — Max Dupré la Tour, Adrian Vetta, et al. · Proceedings of the AAAI Conference on Artificial Intelligence (2025) | TGRS Research Map | TGRS