Abstract
Personality research on social media is a hot topic recently due to the rapid development of social medias well as the central importance of personality in psychology, but it is hard to acquire adequate appropriate labeled samples. Our research aims to choose the right users to be labeled to improve the accuracy of predicting. Given a set of Microblog users’ public information (e.g., number of followers) and a few labeled users, the task is to predict personality of other unlabeled users. The active learning regression algorithm has been employed to establish predicting model in this paper, and the experimental results demonstrate our method can fairly well predict the personality of Microblog users.
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© 2015 Springer International Publishing Switzerland
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Liu, X., Nie, D., Bai, S., Hao, B., Zhu, T. (2015). Personality Prediction for Microblog Users with Active Learning Method. In: Zu, Q., Hu, B., Gu, N., Seng, S. (eds) Human Centered Computing. HCC 2014. Lecture Notes in Computer Science(), vol 8944. Springer, Cham. https://doi.org/10.1007/978-3-319-15554-8_4
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DOI: https://doi.org/10.1007/978-3-319-15554-8_4
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