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.
social media, e-commerce websites, consumption preferences, topic model
E-Commerce | Social Media
Data Management and Analytics
IEICE Transactions on Information and Systems
Institute of Electronics, Information and Communication Engineers
LI, Yang; JIANG, Jing; and LIU, Ting.
Inferring user consumption preferences from social media. (2017). IEICE Transactions on Information and Systems. E100D, (3), 537-545. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/3813
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.