On the Graph Theory of Majority Illusions
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN: 1611-3349, Vol: 14282 LNAI, Page: 17-31
2023
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
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Conference Paper Description
The popularity of an opinion in one’s direct circles is not necessarily a good indicator of its popularity in one’s entire community. For instance, when confronted with a majority of opposing opinions in one’s circles, one might get the impression that one belong s to a minority. From this perspective, network structure makes local information about global properties of the group potentially inaccurate. However, the way a social network is wired also determines what kind of information distortion can actually occur. In this paper, we discuss which classes of networks allow for a majority of agents to have the wrong impression about what the majority opinion is, that is, to be in a ‘majority illusion’.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85172012321&origin=inward; http://dx.doi.org/10.1007/978-3-031-43264-4_2; https://link.springer.com/10.1007/978-3-031-43264-4_2; https://dx.doi.org/10.1007/978-3-031-43264-4_2; https://link.springer.com/chapter/10.1007/978-3-031-43264-4_2
Springer Science and Business Media LLC
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