Abstract
Social media like Facebook, WeChat, YouTube, Weibo and twitter, which generated a huge amount of data every second, which push forward the research about behavior and interactions, such us personality computation. Although personality recognition on social media is of growing interest, past research has not directly examined its potential values in eastern cultural circumstances. Besides, current researchers generally use user-generated information, mainly texts or pictures posted by users, which has caused serious data scandal last year. The present study proposes that privacy friendly personality recognition can be built in practice based on a case study of Chinese personality on WeChat. We use less user-generated information to better protect user privacy and explore the Chinese WeChat users’ personalities. The accuracy of our experiments is 54–67%, which verifies the effectiveness of this scheme. Implications of the function of privacy-friendly personality recognition and other future directions are discussed.
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Acknowledgement
Portions of this work were done while the first author was interning at WeChat, Tencent. We thank Qian Chen, Susan Chen from Tencent.
Funding
This study was funded by the Humanities and Social Sciences Foundation of China Ministry of Education (18YJAZH065), the RD program of Shenzhen (JCYJ20170307153032483, JCYJ20170817161546744), Shenzhen Key Research Base of Humanities and Social Sciences and the Interdisciplinary Research Project of Graduate School of Shenzhen of Tsinghua University (JC2017005).
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Xiong, Q., Ni, S., Xu, Y., Zhang, Q., Peng, K. (2020). Privacy-Friendly Personality Recognition in Social Media: A Case Study of Chinese WeChat Users. In: Abawajy, J., Choo, KK., Islam, R., Xu, Z., Atiquzzaman, M. (eds) International Conference on Applications and Techniques in Cyber Intelligence ATCI 2019. ATCI 2019. Advances in Intelligent Systems and Computing, vol 1017. Springer, Cham. https://doi.org/10.1007/978-3-030-25128-4_263
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