Cross-lingual sentiment analysis with BERT

Thesis title: Cross-lingual sentiment analysis with BERT
Author: Amini Riseh, Mohsen
Thesis type: Diploma thesis
Supervisor: Kliegr, Tomáš
Opponents: Vajdečka, Peter
Thesis language: English
Abstract:
This thesis focuses on the use of the BERT model in sentiment analysis, a task that encompasses a variety of related topics. As such, this work provides an overview of some of the most important associated topics and classical approaches in this field. It begins with a brief introduction to the task of sentiment analysis and its subtasks, including opinion source identification, followed by a discussion of the most common approaches in this domain. A review of related works follows, including an... show full abstract
Keywords: Sentiment Analysis; Transformer Models; BERT; Opinion Mining
Thesis title: Cross-lingual sentiment analysis with BERT
Author: Amini Riseh, Mohsen
Thesis type: Diplomová práce
Supervisor: Kliegr, Tomáš
Opponents: Vajdečka, Peter
Thesis language: English
Abstract:
This thesis focuses on the use of the BERT model in sentiment analysis, a task that encompasses a variety of related topics. As such, this work provides an overview of some of the most important associated topics and classical approaches in this field. It begins with a brief introduction to the task of sentiment analysis and its subtasks, including opinion source identification, followed by a discussion of the most common approaches in this domain. A review of related works follows, including an... show full abstract
Keywords: BERT; Sentiment Analysis; Opinion Mining; Transformer Models

Information about study

Study programme: Information Systems Management
Type of study programme: Magisterský studijní program
Assigned degree: Ing.
Institutions assigning academic degree: Vysoká škola ekonomická v Praze
Faculty: Faculty of Informatics and Statistics
Department: Department of Information and Knowledge Engineering

Information on submission and defense

Date of assignment: 22. 10. 2021
Date of submission: 26. 6. 2024
Date of defense: 28. 8. 2024
Identifier in the InSIS system: https://insis.vse.cz/zp/78500/podrobnosti

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