Name
Abstract | ||
|---|---|---|
In this paper, we describe a novel approach to investigate negative behavior dynamics in online social networks as epidemic phenomena. We present a finite-state machine model for time-varying epidemic dynamics, and validate this model with experiments over a large dataset of Youtube commentaries, indicating how different epidemic patterns of behavior can be tied to specific interaction patterns among users. A full version of this paper is available on arXiv.org. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1145/2808797.2809334 | ASONAM |
Field | DocType | Citations |
Viral marketing,Social network,Epidemic model,Computer science,Heuristic (computer science),Epidemic dynamics,Artificial intelligence,Hidden Markov model,Machine learning | Conference | 1 |
PageRank | References | Authors |
0.35 | 2 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cong Liao | 1 | 9 | 3.57 |
| Anna Cinzia Squicciarini | 2 | 1301 | 106.30 |
| Christopher Griffin | 3 | 58 | 11.43 |
| Sarah Michele Rajtmajer | 4 | 31 | 10.06 |