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Deep learning-based personality recognition from text posts of online social networks

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Abstract

Personality is an important psychological construct accounting for individual differences in people. Computational personality recognition from online social networks is gaining increased research attention in recent years. However, the majority of existing methodologies mainly focused on human-designed shallow statistical features and didn’t make full use of the rich semantic information in user-generated texts, while those texts are exactly the most direct way for people to translate their internal thoughts and emotions into a form that others can understand. This paper proposes a deep learning-based approach for personality recognition from text posts of online social network users. We first utilize a hierarchical deep neural network composed of our newly designed AttRCNN structure and a variant of the Inception structure to learn the deep semantic features of each user’s text posts. Then we concatenate the deep semantic features with the statistical linguistic features obtained directly from the text posts, and feed them into traditional regression algorithms to predict the real-valued Big Five personality scores. Experimental results show that the deep semantic feature vectors learned from our proposed neural network are more effective than the other four kinds of non-trivial baseline features; the approach that utilizes the concatenation of our deep semantic features and the statistical linguistic features as the input of the gradient boosting regression algorithm achieves the lowest average prediction error among all the approaches tested by us.

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Notes

  1. http://mypersonality.org

  2. http://www.liwc.net

  3. https://code.google.com/p/word2vec/

  4. https://radimrehurek.com/gensim/

  5. http://scikit-learn.org/stable/

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Acknowledgements

This work was support by the scientific research funds of PLA (Grant No. AWS13J003). The authors would like to thank the anonymous reviewers for their careful review and constructive comments. Thanks also to David Stillwell, Michal Kosinski and the myPersonality project for their efforts on collecting the Facebook dataset.

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Authors and Affiliations

  1. Army Engineering University, Nanjing, 210007, China

    Di Xue, Lifa Wu, Zheng Hong & Zhiyong Wu

  2. Institute of North Electronic Equipment, Beijing, 100083, China

    Shize Guo & Liang Gao

  3. Electronic Engineering Institute, Hefei, 230037, China

    Xiaofeng Zhong

  4. Hefei University of Technology, Hefei, 230009, China

    Jianshan Sun

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  1. Di Xue
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  2. Lifa Wu
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  3. Zheng Hong
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  7. Xiaofeng Zhong
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Correspondence to Zheng Hong.

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Xue, D., Wu, L., Hong, Z. et al. Deep learning-based personality recognition from text posts of online social networks. Appl Intell 48, 4232–4246 (2018). https://doi.org/10.1007/s10489-018-1212-4

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