Computational Personality Analysis: Introduction, Practical by Yair Neuman PDF

By Yair Neuman

ISBN-10: 3319424580

ISBN-13: 9783319424583

ISBN-10: 3319424602

ISBN-13: 9783319424606

The emergence of clever applied sciences, subtle ordinary language processing methodologies and large textual repositories, invitations a brand new technique for the problem of immediately deciding upon character dimensions during the research of textual information. This brief publication goals to (1) introduce the problem of computational character research, (2) current a different method of character research and (3) illustrate this procedure via case stories and worked-out examples.

This publication is of designated relevance to psychologists, specifically these attracted to the hot insights provided by way of new computational and data-intensive instruments, and to computational social scientists drawn to human character and language processing.

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2013). Computational personality analysis is usually considered to be an implementation of machine learning for the measurement and classification of personality types. Therefore, a very short introduction to machine learning is a must. Machine learning (ML) involves the attempt to gain an abstract representation of a phenomenon from examples in order to efficiently address new future cases. More specifically, we build a model out of training examples such that it can be generalized to new cases and can successfully classify them.

7. 8. 9. 47 Hopeless: hopeless, desperate Lonely: lonely, lonesome Helpless: helpless, defenseless Pain: pain, misery, agony Revengeful: revengeful, vengeful, vindictive Chaotic: chaotic, disordered Unsafe: unsafe, insecure Abandoned: abandoned, deserted Humiliated: humiliated, shamed.

Taking the all above-mentioned ideas and results a step further, my colleagues and I asked whether it is possible to classify songs into their various music genres by measuring the similarity of their lyrics to the personality vectors we used in Neuman and Cohen (2014). We used the k-nearest-neighbors algorithm (KNN) for the classification procedure and each time asked whether a song belongs to a certain music genre by using our personality vectors. In other words, we asked the classifier to make a binary decision about whether a song belongs to a certain music genre or not, based on the similarity of its lyrics to each of several personality vectors.

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Computational Personality Analysis: Introduction, Practical Applications and Novel Directions by Yair Neuman


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