Personalized news recommendation based on click behavior
Proceedings of the 15th international conference on Intelligent user interfaces
Short and tweet: experiments on recommending content from information streams
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Time is of the essence: improving recency ranking using Twitter data
Proceedings of the 19th international conference on World wide web
Earthquake shakes Twitter users: real-time event detection by social sensors
Proceedings of the 19th international conference on World wide web
Recommending twitter users to follow using content and collaborative filtering approaches
Proceedings of the fourth ACM conference on Recommender systems
You are where you tweet: a content-based approach to geo-locating twitter users
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Computing political preference among twitter followers
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Semantic enrichment of twitter posts for user profile construction on the social web
ESWC'11 Proceedings of the 8th extended semantic web conference on The semanic web: research and applications - Volume Part II
Interweaving Trend and User Modeling for Personalized News Recommendation
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
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In this paper, we study user modeling on Twitter. We investigate different strategies for mining user interest profiles from microblogging activities ranging from strategies that analyze the semantic meaning of Twitter messages to strategies that adapt to temporal patterns that can be observed in the microblogging behavior. We evaluate the quality of the user modeling methods in the context of a personalized news recommendation system. Our results reveals that an understanding of the semantic meaning of microposts is key for generating high-quality user profiles.