Design and Development of a Personality Traits Classifier based on Machine Learning Techniques

Benito Sánchez, Diego (2017). Design and Development of a Personality Traits Classifier based on Machine Learning Techniques. Proyecto Fin de Carrera / Trabajo Fin de Grado, E.T.S.I. Telecomunicación (UPM).

Description

Title: Design and Development of a Personality Traits Classifier based on Machine Learning Techniques
Author/s:
  • Benito Sánchez, Diego
Contributor/s:
  • Iglesias Fernández, Carlos Ángel
Item Type: Final Project
Degree: Grado en Ingeniería de Tecnologías y Servicios de Telecomunicación
Date: 2017
Subjects:
Freetext Keywords: YouTube, Scikit-learn, Machine Learning, NLP, Personality Traits, Python, NLTK, Senpy, Sentiments and Emotions.
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Ingeniería de Sistemas Telemáticos [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Recently, during the last few years the use of digital devices, with Internet access, such as smartphones or tablets, has been increasing considerably in people's day after day. Because of this, Internet usage and therefore social networks usage has also increased. In social networks, users share personal data to broadcast content between users and this also implicitly convey useful information for companies studies. This makes interesting the task of characterizing users (in this case using personality) through their activity in social networks. In previous studies, there has been seen that personality can affect users in different aspects: preferences for interaction styles in the digital world or musical genres, for example. Consequently, the design of customized user interfaces and music recommender systems can help us to provide better experiences to users. This thesis is the result of a project whose main aim has been to obtain a personality traits classifier, whose task was set in a workshop in 2014, working on a YouTube dataset, using Python as programming language and deploying the system as a Senpy plug-in. During the development phase, there have been used supervised machine learning tools, natural language processing techniques (NLP) and queries to the sentiments and emotions analysis platform, Senpy. Regarding the workshop, there have been obtained similar results, what means that predicting personality can be seen as a real possibility.

More information

Item ID: 47542
DC Identifier: http://oa.upm.es/47542/
OAI Identifier: oai:oa.upm.es:47542
Deposited by: Biblioteca ETSI Telecomunicación
Deposited on: 28 Aug 2017 05:58
Last Modified: 28 Aug 2017 05:58
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