Automatic Generation of Personalized Annotation Tags for Twitter Users

This paper introduces a system designed for automatically generating personalized annotation tags to label Twitter user's interests and concerns. We applied TFIDF ranking and TextRank to extract keywords from Twitter messages to tag the user. The user tagging precision we obtained is comparable to the precision of keyword extraction from web pages for content-targeted advertising.

• Type: Journal
• Year: 2010
• Where: NAACL
• Authors: Wei Wu, Bin Zhang, Mari Ostendorf
• Keywords: Annotation Tags, Computational Linguistics, NAACL 2010, Twitter Messages, Twitter User