Predicting Personality Traits from Physical Activity Intensity

Publication Year: 2019 Publication Type : JournalArticle


Call and messaging logs from mobile devices have been used to predict human personality traits successfully in re-cent years. However, the widely available accelerometer data is not yet utilized for this purpose. In this research, we explored some important features describing human physi-cal activity intensity, used for the very first time to predict human personality traits through raw accelerometer data. Using a set of newly introduced metrics, we combined phys-ical activity intensity features with traditional phone activity features for personality prediction. The experiment results show that the predicted personality scores are closer to the ground truth, with observable reduction of errors in predict-ing the Big-5 personality traits across male and female.


@article{DBLP:journals/corr/abs-1906-07864, archiveprefix = {arXiv},
    author = {Nan Gao and Wei Shao and Flora D. Salim},
    bibsource = {dblp computer science bibliography,},
    biburl = {},
    eprint = {1906.07864},
    journal = {CoRR},
    timestamp = {Mon, 24 Jun 2019 01:00:00 +0200},
    title = {Predicting Personality Traits from Physical Activity Intensity},
    url = {},
    volume = {abs/1906.07864},
    year = {2019}


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