Name
Abstract | ||
|---|---|---|
Information diffusion is a natural phenomenon occurring in social networks. The adoption behavior of a node toward an information piece in a social network can be affected by different factors, e.g., freshness and hotness. Previously, many diffusion models are proposed to consider one or several fixed factors. In fact, the factors affecting adoption decision of a node are different from one to ano... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TKDE.2017.2786209 | IEEE Transactions on Knowledge and Data Engineering |
Keywords | Field | DocType |
Social network services,Integrated circuit modeling,Predictive models,Estimation,Uncertainty,Adaptation models | Social network,Computer science,Natural phenomenon,Artificial intelligence,Diffusion (business),Machine learning | Journal |
Volume | Issue | ISSN |
30 | 7 | 1041-4347 |
Citations | PageRank | References |
2 | 0.36 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chung-Kuang Chou | 1 | 25 | 5.52 |
| Ming Chen | 2 | 6507 | 1277.71 |