Abstract
Occasionaly, every society needs to reach a decision among its members. For this, it may use a voting mechanism, i.e., collect the votes of the group members and output a decision that best expresses the group's will. To make up their minds, individuals often discuss the issue with friends before taking their votes, thus mutually affecting each other's votes. Individuals are also, to some extent, influenced by the opinions of key figures in their culture, such as politicians, publicists, etc., commonly considered as the “elite” of the society. This work studies the “power of the elite”: to what extent can the elite of a social network influence the rest of society to accept its opinion, and thus become a monopoly. We present an empirical study of local majority voting in social networks, where the elite forms a coalition against all other (common) nodes. The results, obtained on several social networks, indicate that an elite of size m (where m is the number of connections) has disproportionate power, relative to its size, with respect to the rest of society: it wins the majority voting and remains stable over time.
Original language | English |
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Title of host publication | ICDCN 2019 - Proceedings of the 2019 International Conference on Distributed Computing and Networking |
Publisher | Association for Computing Machinery |
Pages | 342-351 |
Number of pages | 10 |
ISBN (Electronic) | 9781450360944 |
DOIs | |
State | Published - 4 Jan 2019 |
Externally published | Yes |
Event | 20th International Conference on Distributed Computing and Networking, ICDCN 2019 - Bangalore, India Duration: 4 Jan 2019 → 7 Jan 2019 |
Publication series
Name | ACM International Conference Proceeding Series |
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Conference
Conference | 20th International Conference on Distributed Computing and Networking, ICDCN 2019 |
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Country/Territory | India |
City | Bangalore |
Period | 4/01/19 → 7/01/19 |
Bibliographical note
Publisher Copyright:© 2019 Association for Computing Machinery.
Keywords
- Elites
- Majority Vote
- Monopolies
- Social Networks