Abstract
In recent years, the number of social networks users has shown explosive growth. In this context, social media provides researchers with plenty of information about user behavior and social behavior. We are beginning to understand user’s behavior on social media is related to user’s personality. Conventional personality assessment depends on self-report inventory, which costs a lot to collect information. This paper tries to predict user’s Big-Five personality through their information on social networks. We conducted a Big-Five personality inventory test with 131 users of Chinese social network Sina Weibo, and crawled all of their Weibo texts and profile information. By studying the relevance between all types of user generated information and personality results of users, we extracted five most relative dimensionalities and used machine learning method to successfully predict the Big-Five personality of users.
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Wan, D., Zhang, C., Wu, M., An, Z. (2014). Personality Prediction Based on All Characters of User Social Media Information. In: Huang, H., Liu, T., Zhang, HP., Tang, J. (eds) Social Media Processing. SMP 2014. Communications in Computer and Information Science, vol 489. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45558-6_20
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DOI: https://doi.org/10.1007/978-3-662-45558-6_20
Publisher Name: Springer, Berlin, Heidelberg
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