Application of Text Mining in Personality Tests for Recruiting
Liset Marleen Pak
This thesis describes how text mining methods have been applied to analyse self-description texts given in the context of personality tests that are used by Estonian HR-company Psience OÜ. The aim of the thesis is to use probabilistic topic modelling algorithm called latent Dirichlet allocation (LDA) to analyse the texts and to compare the results with the scores of the personality tests. As a result of applying topic modelling techniques, three topics where found that allowed to describe the personality test takers by their word use. Also, the comparative analysis showed that refined version of topic modelling approach could help to make the text analysis more automatic in the future as it is today.
Graduation Thesis language
Graduation Thesis type
Master - Conversion Master in IT