Abstract
Social Networks have developed so fast recently, and the most popular one in China is Renren, with 200 million members until 2012. In this study, we propose to determine personality traits based on Renren status usage behavior. Renren status is a short text published by the user like micro-blog and is available for all registered users. We extract behavior features from Renren status, and calculate the correlation between “Big Five” personality traits and the status usage. More than two hundred graduate students participated in our experiment. We get their authorizations to collect their status content using Renren APIs. Comparing to the classical self-reported personality analysis, we demonstrate via experimental studies that users’ personalities have a significant correlation with status usage. Results show that some significant correlations exist between status content and personality type.
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Bai, S., Gao, R., Zhu, T. (2012). Determining Personality Traits from Renren Status Usage Behavior. In: Hu, SM., Martin, R.R. (eds) Computational Visual Media. CVM 2012. Lecture Notes in Computer Science, vol 7633. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34263-9_29
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DOI: https://doi.org/10.1007/978-3-642-34263-9_29
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