Abstract
Microblog messages display gender tendency to some extent, so automatic identification of gender of microblog users with message content mining techniques is studied. A novel approach is proposed to identify microblog user gender. The proposed approach extracts three types of features, i.e., characteristic item features, stylometry features and medium diversity features, from microblog messages with high gender-relatedness, and utilizes a series of pattern recognition techniques, such as feature normalization, feature selection and SVM, to detect microblogger gender. Massive experiments demonstrate that the effectiveness of the proposed approach.
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Huang, F., Li, C., Lin, L. (2014). Identifying Gender of Microblog Users Based on Message Mining. In: Li, F., Li, G., Hwang, Sw., Yao, B., Zhang, Z. (eds) Web-Age Information Management. WAIM 2014. Lecture Notes in Computer Science, vol 8485. Springer, Cham. https://doi.org/10.1007/978-3-319-08010-9_54
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DOI: https://doi.org/10.1007/978-3-319-08010-9_54
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08009-3
Online ISBN: 978-3-319-08010-9
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