Abstract
In this paper, anonymized mobile phone log data have been used to predict users’ personality in the context of Big5 model in a privacy-preserving manner. First, the Big5 concepts are presented. Afterwards, we present how to calculate Big5 indicators from the available mobile data sets. Hereafter, Big5 traits can be predicted based on those just-specified indicators. As a proof of our concepts, implementation results will be presented in the context of TB5 (Tracking Big5) tool, which has been designed and developed to predict Big5 personalities in a representative manner.
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Acknowledgments
Thanks to Orange Sonatel Senegal and the D4D team for providing the mobile phone data. Support from the Duy Tan University, Vietnam is acknowledged.
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Nguyen, B.T., Dung, D.N., Thuy, H.N.T., Thi, T.H., Huong, L.P.T., Dinh, H.T. (2020). Tracking Big5 Traits Based on Mobile User Log Data. In: Satapathy, S., Bhateja, V., Nguyen, B., Nguyen, N., Le, DN. (eds) Frontiers in Intelligent Computing: Theory and Applications. Advances in Intelligent Systems and Computing, vol 1013. Springer, Singapore. https://doi.org/10.1007/978-981-32-9186-7_25
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DOI: https://doi.org/10.1007/978-981-32-9186-7_25
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