Name
Abstract | ||
|---|---|---|
Influence propagation is a significant issue in social network analysis. Existing works that studied this problem usually committed to looking for the important individuals of a social network, while very few study focuses on the overall propagation performance of the network. The overall propagation performance plays a key role in the development of a social network. In this paper, we study the notion of social cohesion that is based on influence propagation. We analyze the structure of the network and identify the key factors that affect the propagation efficiency. In order to improve the propagation efficiency, we further propose an efficient heuristic to improve propagation efficiency via relationships building. Finally we have also conducted experiment and the results demonstrate the superiority of our heuristic. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/CANDAR.2019.00025 | 2019 Seventh International Symposium on Computing and Networking (CANDAR) |
Keywords | Field | DocType |
social network, cohesion, K-shell decomposition, connectivity | Cohesion (chemistry),Heuristic,Influence propagation,Social network,Computer science,Social network analysis,Risk analysis (engineering) | Conference |
ISSN | ISBN | Citations |
2379-1888 | 978-1-7281-4726-0 | 0 |
PageRank | References | Authors |
0.34 | 10 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ruochen Jiang | 1 | 0 | 0.34 |
| Jiamou Liu | 2 | 49 | 23.19 |
| Chen Wu | 3 | 177 | 19.51 |