{"type":"ScholarlyArticle","title":"Twitter-Based User Modeling for News Recommendations","authors":[{"name":"Fabian Abel","slug":"fabian-abel","given":"Fabian","family":"Abel","affiliation":""},{"name":"Qi Gao","slug":"qi-gao","given":"Qi","family":"Gao","affiliation":""},{"name":"Geert-Jan Houben","slug":"geert-jan-houben","given":"Geert-Jan","family":"Houben","affiliation":""},{"name":"Ke Tao","slug":"ke-tao","given":"Ke","family":"Tao","affiliation":""}],"abstract":"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.","doi":null,"url":"https://ijcai.org/proceedings/2013/437","pdf":"https://ijcai.org/proceedings/2013/0437.pdf","markdown":"https://ijcai.org/proceedings/2013/437.md","bibtex":"https://ijcai.org/proceedings/2013/bibtex/437","volume":{"slug":"2013","title":"Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2013","url":"https://ijcai.org/proceedings/2013/","year":2013,"location":"Beijing, China","dates":"3–9 August 2013","editors":"Francesca Rossi","isbn":"978-1-57735-633-2","publisher":"AAAI Press / International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":437,"pages":{"first":2962,"last":2965},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}