Chapter

Advances in Soft Computing and Its Applications

Volume 8266 of the series Lecture Notes in Computer Science pp 484-496

Common Sense Knowledge Based Personality Recognition from Text

  • Soujanya PoriaAffiliated withNanyang Technological UniversityJadavpur University
  • , Alexandar GelbukhAffiliated withCIC, Instituto Politecnico NacionalInstitute for Modern Linguistic Research, “Sholokhov” Moscow State University for Humanities
  • , Basant AgarwalAffiliated withMalaviya National Institute of Technology
  • , Erik CambriaAffiliated withNanyang Technological University
  • , Newton HowardAffiliated withMassachusetts Institute of Technology

* Final gross prices may vary according to local VAT.

Get Access

Abstract

Past works on personality detection has shown that psycho-linguistic features, frequency based analysis at lexical level, emotive words and other lexical clues such as number of first person or second person words carry major role to identify personality associated with the text. In this work, we propose a new architecture for the same task using common sense knowledge with associated sentiment polarity and affective labels. To extract the common sense knowledge with sentiment polarity scores and affective labels we used Senticnet which is one of the most useful resources for opinion mining and sentiment analysis. In particular, we combined common sense knowledge based features with phycho-linguistic features and frequency based features and later the features were employed in supervised classifiers. We designed five SMO based supervised classifiers for five personality traits. We observe that the use of common sense knowledge with affective and sentiment information enhances the accuracy of the existing frameworks which use only psycho-linguistic features and frequency based analysis at lexical level.

Keywords

personality detection common sense knowledge affective and sentiment information