Computational Personality Analysis: Introduction, Practical by Yair Neuman

By Yair Neuman

The emergence of clever applied sciences, subtle normal language processing methodologies and enormous textual repositories, invitations a brand new technique for the problem of instantly picking out character dimensions in the course of the research of textual facts. This brief booklet goals to (1) introduce the problem of computational character research, (2) current a special method of character research and (3) illustrate this technique via case reports and worked-out examples.

This ebook is of detailed relevance to psychologists, particularly these attracted to the recent insights provided by way of new computational and data-intensive instruments, and to computational social scientists attracted to human character and language processing.

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For example, Langmeyer et al. e. the openness dimension of the Big Five) prefer complex music. If you think about it, this makes a lot of sense. If you are an extravert who is full of energy, you will probably prefer a music style that adheres to your temper. However, in our study, we were interested in the lyrics of various music genres, which is a much more delicate issue. Our first study asked whether and how the words used by different personality types are similar to the words used by different music genres.

This is precisely the logic that guided my vectorial semantics approach to personality recognition (Neuman and Cohen 2014) and it can Fig. 1 A 2D representation of “depressed” Fig. 1 Vectors of Personality 41 be summarized by the following steps: (1) based on theoretical and/or empirical knowledge, identify a set of words that represent a psychological trait; (2) represent this set as a vector; (3) choose a text you would like to assess and represent its words as a vector; and (4) measure the similarity between the two vectors by using a vector space.

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