Fluidspread: A New Method of Maximizing Positive Influence in Online Social Networks via Fluid Dynamics
2020
Influence maximization aims at detecting the top-k influential users in online social networks. Almost all previous models of influence spread cannot simultaneously incorporate users’ attitudes, interactions between users, and dynamic influences. However, in this study, we established a new model of influence spread via fluid dynamics, which reveals the time-evolving process for influence spread. We modeled the spread of influence as the process of fluid update based on three dimensions: the difference of fluid height, the temperature of fluids, and the difference of temperature. Moreover, we formulated the problem of maximizing positive influence and devised a Fluid-spread greedy algorithm to solve it. We conducted extensive comparisons between our approach and several baselines, and experimental results illustrate the effectiveness and efficiency of the Fluidspread model and algorithm.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
18
References
0
Citations
NaN
KQI