Ensemble Methods for Personality Recognition

Authors

  • Ben Verhoeven University of Antwerp
  • Walter Daelemans University of Antwerp
  • Tom De Smedt University of Antwerp

DOI:

https://doi.org/10.1609/icwsm.v7i2.14465

Keywords:

computational stylometry, personality recognition

Abstract

An important bottleneck in the development of accurate and robust personality recognition systems based on supervised machine learning, is the limited availability of training data, and the high cost involved in collecting it. In this paper, we report on a proof of concept of using ensemble learning as a way to alleviate the data acquisition problem. The approach allows the use of information from datasets from different genres, personality classification systems and even different languages in the construction of a classifier, thereby improving its performance. In the exploratory research described here, we indeed observe the expected positive effects.

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Published

2021-08-03

How to Cite

Verhoeven, B., Daelemans, W., & De Smedt, T. (2021). Ensemble Methods for Personality Recognition. Proceedings of the International AAAI Conference on Web and Social Media, 7(2), 35-38. https://doi.org/10.1609/icwsm.v7i2.14465