Takayasu Fushimi
ABSTRACT
In this research, we propose a Voter Model introducing expertise weights and friendshipness weights, which is an opinion formation model more suitable to the reality. Since the conventional Voter Model uniformly handles the following users, it is a model that adopts the opinion of the majority of follow users. When choosing an item from some alternatives, the adoption probability is determined by a majority vote. However, when actually making decisions, it is natural to consider the opinions of users who have expert knowledge about target products. Therefore, in this research, we propose a model that reflects the fact that the opinions of follow users are not handled equally, but the opinion of users with high specialty is preferentially selected. Specifically, we quantify the expertise of the user and introduce adoption probability proportional to expertise. Also, at the time of user's decision, it is natural to consider the opinion of users who have similar features such as profiles and circumstances with themselves. Therefore, in this research, we also propose a model reflecting the fact that users' opinions of users with high friendshipness are preferentially selected. In our experimental evaluation, actual data including user's following relationship, user profile, and categories of review items, at the cosmetic site @cosme are used. In the ranking of expected influence degree calculated by the proposed method, we quantitatively evaluate whether reviews of highly ranked users influence other users. We also evaluate how much the ranking result differs from the conventional Voter Model and centrality rankings.
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Index Terms
- Modeling Opinion Formation by Incorporating Users' Expertise and Friendshipness
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