What is he/she like?: Estimating Twitter user attributes from contents and social neighbors

We propose a new method for estimating user attributes (gender, age, occupation, and interests) of a Twitter user from the user's contents (profile document and tweets) and social neighbors, i.e. those whom the user has mentioned. Our labeling method is able to collect a large amount of trainin...

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Bibliographic Details
Published in2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013) pp. 1448 - 1450
Main Authors Ito, Jun, Hoshide, Takahide, Toda, Hiroyuki, Uchiyama, Tadasu, Nishida, Kyosuke
Format Conference Proceeding
LanguageEnglish
Published ACM and IEEE 01.08.2013
Subjects
Accuracy
Blogs
Estimation
Labeling
Manuals
Training data
Twitter
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Summary:We propose a new method for estimating user attributes (gender, age, occupation, and interests) of a Twitter user from the user's contents (profile document and tweets) and social neighbors, i.e. those whom the user has mentioned. Our labeling method is able to collect a large amount of training data automatically by using Twitter users associated with a blog account. Furthermore, we experiment estimation methods using social neighbors with three adjustable levels of its information and show that our method, which uses the target user's profile document and tweets and the neighbors' profile documents (not including tweets), achieves the best accuracy.
DOI:10.1145/2492517.2492585