Machine learning techniques for sentiment analysis
Year: 2024
Type: article
Abstract: Sentiment analysis stands out as one of the most dynamic and pivotal areas in the field of natural language processing. In this work, a range of machine learning strategies has been proposed, applied, and benchmarked for sentiment analysis, with a specific focus on supervised machine learning techniques. Various algorithms have been considered and applied to texts extracted from Twitter. Furthermore, the results are compared with works that applied unsupervised machine learning techniques to the same dataset.
Authors: Jessica Olivares Lopez, Abraham Sánchez López, Rogelio González Velázquez, María del Carmen Santiago Díaz, Ana Claudia Zenteno Vázquez
Institution: Benemérita Universidad Autónoma de Puebla
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4404851703