After the impressive diffusion of social media and microblogging websites of the last years, the identification of users having the capability of influencing other users’ choices has becoming an important research topic because of the opportunities it can offer to many business companies. We proposed to model the contents of tweets posted by users to express opinions on items with a three-layer network. Layers represent users, items, and keywords, along with intra-layer interactions among the actors of the same layer. Inter-layer connections are triples (u,i,k) expressing the information that a user u comments on an item i by using a keyword k. By exploiting multilinear algebra, we present a method capable to extract the most active users stating their point of view about dominant items tagged with dominant keywords. Experiments on two real use cases show the ability of the approach to find influential users very active in posting opinions about the topic of interest.
Edge of tensor: 26673
Dataset TV Series:
TV Series: 12
Edge of tensor: 51534
Edge of tensor: from 10K to 100K by step 10K