Formal models of opinion formation and their application to real data
Evidence From Online Social Networks
Bibliographic Data
| ID | 7529916 |
|---|---|
| Authors | Ivan Kozitsin (0000-0002-2638-0131, Laboratory of Complex Networks, V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, Moscow, Russian Federation, corresponding author) |
| Year | 2020 |
| Volume | 46 |
| Issue | 2 |
| Pages | 120-147 |
| Publication date | 2020-10-29 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Mathematical Sociology (JOURNAL) |
| Journal identifiers | ISSN: 0022-250X • E-ISSN: 1545-5874 |
| Publisher | Taylor & Francis (PUBLISHER • GB) |
| DOI | 10.1080/0022250x.2020.1835894 |
| OpenAlex | W3095217883 |
| Language | EN |
| Citations received | 6 |
| References cited | 40 |
In this paper, we analyze data on the opinion dynamics of 1,660,927 users of an online social network using formal models of opinion formation. We have observed that moderate users have a tendency to follow the average opinion of their online friends, which we interpret as a presence of bounded confidence. Further, we have discovered that the probability of moving toward the average opinion goes down if the difference between it and the user’s opinion is too large. Another interesting feature uncovered is that if a user’s opinion and the average opinion of their online friends are very similar, the influence also decreases
Data science · Internet privacy · Social media · Social network (sociolinguistics · World Wide Web · Complex Network Analysis Techniques · Computer Science · Misinformation and Its Impacts · Opinion Dynamics and Social Influence
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| Citations per year | 1.2 |
|---|---|
| Citation span | 2021 - 2026 (6) |
| Highly cited | No |