Name
Abstract | ||
|---|---|---|
ABSTRACTAs an important factor governing opinion dynamics, stubbornness strongly affects various aspects of opinion formation. However, a systematically theoretical study about the influences of heterogeneous stubbornness on opinion dynamics is still lacking. In this paper, we study a popular opinion model in the presence of inhomogeneous stubbornness. We show analytically that heterogeneous stubbornness has a great impact on convergence time, expressed opinion of every node, and the overall expressed opinion. We provide an explanation of the expressed opinion in terms of stubbornness-dependent spanning diverging forests. We propose quantitative indicators to quantify some social concepts, including conflict, disagreement, and polarization by incorporating heterogeneous stubbornness, and develop a nearly linear time algorithm to approximate these quantities, which has a proved theoretical guarantee for the error of each quantity. To demonstrate the performance of our algorithm, we perform extensive experiments on a large set of real networks, which indicate that our algorithm is both efficient and effective, scalable to large networks with millions of nodes. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1145/3511808.3557304 | Conference on Information and Knowledge Management |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wanyue Xu | 1 | 1 | 3.07 |
| Liwang Zhu | 2 | 0 | 0.34 |
| Jiale Guan | 3 | 0 | 0.34 |
| Zuobai Zhang | 4 | 1 | 2.39 |
| Zhongzhi Zhang | 5 | 85 | 22.02 |