Inferring User Consumption Preferences from Social Media

Yang LI  Jing JIANG  Ting LIU  

IEICE TRANSACTIONS on Information and Systems   Vol.E100-D   No.3   pp.537-545
Publication Date: 2017/03/01
Publicized: 2016/12/09
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2016EDP7265
Type of Manuscript: PAPER
Category: Artificial Intelligence, Data Mining
social media,  e-commerce websites,  consumption preferences,  topic model,  

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Social Media has already become a new arena of our lives and involved different aspects of our social presence. Users' personal information and activities on social media presumably reveal their personal interests, which offer great opportunities for many e-commerce applications. In this paper, we propose a principled latent variable model to infer user consumption preferences at the category level (e.g. inferring what categories of products a user would like to buy). Our model naturally links users' published content and following relations on microblogs with their consumption behaviors on e-commerce websites. Experimental results show our model outperforms the state-of-the-art methods significantly in inferring a new user's consumption preference. Our model can also learn meaningful consumption-specific topics automatically.