Abstract
We analyze evolution of trust networks in social media sites from a perspective of mediators. To this end, we propose two stochastic models that simulate the dynamics of creating a trust link under the presence of mediators, the A-ME and A-MAE models, where the A-ME model analyzes mediator effects for trust-network evolution in terms of mediator types, and the A-MAE model, an extension of the A-ME model, analyzes mediator-activity effects for trust-network evolution. We present an efficient method of inferring the values of model parameters from an observed sequence of trust links and user activities. Using real data from Epinions, we experimentally show that the A-MAE model significantly outperforms the A-ME model for predicting trust links in the near future under the presence of mediators, and demonstrate the effectiveness of mediator-activity information for trust-network evolution. We further clarify, by using the A-ME and A-MAE models, several characteristic properties of trust-link creation probability in the Epinions data.
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Hatta, K., Kumano, M., Kimura, M., Saito, K., Ohara, K., Motoda, H. (2014). Analyzing Mediator-Activity Effects for Trust-Network Evolution in Social Media. In: Pham, DN., Park, SB. (eds) PRICAI 2014: Trends in Artificial Intelligence. PRICAI 2014. Lecture Notes in Computer Science(), vol 8862. Springer, Cham. https://doi.org/10.1007/978-3-319-13560-1_24
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DOI: https://doi.org/10.1007/978-3-319-13560-1_24
Publisher Name: Springer, Cham
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