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tfg_nuria_lopez_raich.pdf (1.23 MB)

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Bachelor thesis

Publication date

2022-06-13

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cc-by-nc-nd (c) Núria López Raich, 2022
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/191161

Study of different models for sentiment analysis and language representation

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[en] In this project we study three different models of artificial intelligence to carry out the process of sentiment analysis, which consists of determining the polarity of a text; that is, detecting whether it is positive, negative or neutral. The first model studied is a neural network, specifically a long short-term memory, which uses deep learning techniques. We delve deeper into the study of its structure and operation, unmasking all the mathematics behind it. The other two models belong to machine learning: logistic regression and Naive Bayes. We emphasize the study of its parameters and optimization, with the intention to understand the learning process of each one. Finally, we apply the results and techniques developed to implement a Python program with each model in order to detect the sentiment of thousands of reviews from social media of different bars and restaurants. We dedicate a whole chapter to give the results, the analysis of each one and a comparison between them.

Description

Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2022, Director: Josep Vives i Santa Eulàlia i Jordi Vitrià i Marca

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Models lineals (Estadística), Treballs de fi de grau, Intel·ligència artificial, Aprenentatge automàtic, Tractament del llenguatge natural (Informàtica)

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Linear models (Statistics), Bachelor's theses, Artificial intelligence, Machine learning, Natural language processing (Computer science)

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Treballs Finals de Grau (TFG) - Matemàtiques

Citation

LÓPEZ RAICH, Núria. Study of different models for sentiment analysis and language representation. [consulted: 10 of June of 2026]. Available at: https://hdl.handle.net/2445/191161

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