Please use this identifier to cite or link to this item:
http://hdl.handle.net/10609/81435
Title: | Análisis de sentimientos en Twitter |
Author: | Sobrino Sande, José Carlos |
Director: | Ventura, Carles |
Tutor: | Kanaan-Izquierdo, Samir |
Others: | Universitat Oberta de Catalunya |
Abstract: | The aim of this Master's Thesis is to explain the theoretical foundations over sentiment analysis is seated, its history, applications and its relationship with natural language processing. It will be offered a vision of the state of the art through a tour of the published studies by several authors and we will see the most important methods for developing this kind of solutions. It will be implemented a sentiment classifier for Twitter messages based on supervised learning algorithms and we will elaborate a comparative study with the most popular techniques for sentiment analysis at document level. Finally, we will talk about the future of this kind of systems. |
Keywords: | supervised learning natural language processing machine learning sentiment analysis |
Document type: | info:eu-repo/semantics/masterThesis |
Issue Date: | Jun-2018 |
Publication license: | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Appears in Collections: | Bachelor thesis, research projects, etc. |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
jsobrinosTFM0618memoria.pdf | Memoria del TFM | 2,37 MB | Adobe PDF | View/Open |
Share:
This item is licensed under a Creative Commons License