Detección de estados de ánimo mediante sentiment analysis en hispanohablantes

The following research shows the elaboration and validation of a computational model designed to detect Spanish speakers’ moods from answers entered by these users in text format. It was used the Keyword Spotting Technique (KST) for text treatment, and Sentiment Analysis based on only Natural Language Processing (NLP) concepts for text analysis. A mobile application with chatbot interface and a bot that invites the user to give details about their mood through questions validated by an expert, are the tools used to collect all the conversations. As a result of the pilot test of 30 conversations, and after the final test in the sample of 49 conversations, there is a correct classification of 70% of the cases, as well as a proposal for the treatment of texts in Spanish.

Name thesis:degree_name

Ingeniero de Sistemas

Level thesis:degree_level

Título Profesional

Discipline thesis:degree_discipline

Ingeniería de Sistemas

Grantor dc:publisher

Universidad de Lima

Year dc:date.issued

2019

Author dc:creator

• Morzán Fuentes, Stephany Alessandra

Advisor dc:contributor.advisor

• Gutiérrez Cárdenas, Juan Manuel

• Lenguaje y emociones
• Análisis de texto (Minería de datos)
• Proceso en lenguaje natural (informática)
• Lingüística computacional
• Hispanoamericanos
• Language and emotions
• Text Analysis (Data Mining)
• Natural language processing (computing)
• Computational linguistics
• Hispanic americans

Statement dc:rights

• info:eu-repo/semantics/openAccess

Licence dc:rights.uri

• https://creativecommons.org/licenses/by-nc-sa/4.0/

Language dc:language.iso

spa

DOI

http://doi.org/10.26439/ulima.tesis/11318

OAI identifier oai:identifier

oai:repositorio.ulima.edu.pe:20.500.12724/11318