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).

Descripción

Título: Design and Development of a Personality Traits Classifier based on Machine Learning Techniques
Autor/es:
  • Benito Sánchez, Diego
Director/es:
  • Iglesias Fernández, Carlos Ángel
Tipo de Documento: Proyecto Fin de Carrera/Grado
Grado: Grado en Ingeniería de Tecnologías y Servicios de Telecomunicación
Fecha: 2017
Materias:
Palabras Clave Informales: YouTube, Scikit-learn, Machine Learning, NLP, Personality Traits, Python, NLTK, Senpy, Sentiments and Emotions.
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Ingeniería de Sistemas Telemáticos [hasta 2014]
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

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.

Más información

ID de Registro: 47542
Identificador DC: http://oa.upm.es/47542/
Identificador OAI: oai:oa.upm.es:47542
Depositado por: Biblioteca ETSI Telecomunicación
Depositado el: 28 Ago 2017 05:58
Ultima Modificación: 28 Ago 2017 05:58
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