Tag-Based User Profiling for Social Media Recommendation
Date Issued
2008
Date
2008
Author(s)
Hung, Chia-Chuan
Abstract
Making recommendations for social media presents special challenges. As the fact of tagging becomes a common practice at many social media sites, this research proposes a new approach to user profiling based on the tags associated with one’s personal collection of contents. To utilize the social interaction inherent in tagging, a personal profile can be further extended with the tags specified by one’s social contacts. tag-to-tag matrix is defined to enable collaborative filtering-styled recommendations without explicit user ratings. By looking up this matrix and considering the user’s conceptual associations, we presented the process of making social media recommendations based on the user’s tag-based profile or based on a given tag. A practical implementation is applied on the del.icio.us bookmarks and tags of 17,435 users, and both user profiles and recommendations are generated and evaluated. Our small-scaled user study shows that most of our recommendations satisfied the testers.
Subjects
social media
tag
recommender system
user profile
Type
thesis
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