Publication details
Search for the optimal strategy to spread a viral video: An agent-based model optimized with genetic algorithms
| Authors | |
|---|---|
| Year of publication | 2014 |
| Type | Article in Proceedings |
| Conference | 32nd International Conference Mathematical Methods in Eocnomics Conference Proceedings |
| MU Faculty or unit | |
| Citation | |
| Web | Conference proceedings |
| Field | Economy |
| Keywords | viral video; viral marketing; social network; agent-based model; genetic algorithm |
| Attached files | |
| Description | Agent-based computational papers on viral marketing have been so far focused on the study of the word-of-mouth knowledge diffusion that merges the decisions to adopt a product and to share information about it. This approach is not suitable for the analysis of the viral video sharing because it is shared with no regard whether the sender has adopted the advertised product or not. This paper presents a more realistic model of viral video diffusion in which every agent that viewed the video shares it once with a random subset of her neighbors. The optimal seeding strategy is then searched with genetic algorithms. The seeding strategy found by the genetic algorithm includes into the initial seed the agents with most connections and lowest clustering ratios; some agents are also selected randomly. However, this complex seeding strategy does not perform significantly better than a simple strategy of selecting agents with many connections. |
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