Classifiers and text mining: application to a specific context
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Classifiers and text mining: application to a specific contextAuthor(s)
Directors
Vilares, JesúsAlonso, Miguel A.
Date
2022Center/Dept./Entity
Universidade da Coruña. Facultade de InformáticaDescription
Traballo fin de grao (UDC.FIC). Enxeñaría Informática. Curso 2021/2022Abstract
[Abstract]: The constant growth of social networks has not only brought us new ways of interacting
with each other, but has also given way to a severe increase in negative behaviors: hate
speech, racism, gender harassment, cyberbullying, etc. Manually trying to detect this kind of
behaviours in millions of daily social media posts is out of the question. The solution lies in
developing intelligent systems to automate such detection tasks.
As the nature of these texts is completely subjective, this problem falls under the field
of sentiment analysis, which aims to systematically identify and study affective states and
subjective information in textual data using natural language processing techniques.
In particular, this project is focused on the research of different machine learning techniques
related to natural language processing, in order to automate and perform a reliable
detection and classification of sexist-related behaviours in social media texts. We will tackle
the task of adequately processing the extracted data from social media, as well as researching
various text classification techniques and models that we will use to develop and evaluate a
variety of classifiers.
Keywords
Sentiment analysis
Natural language processing
Machine learning
Text mining
Social networks
Sexist language
Natural language processing
Machine learning
Text mining
Social networks
Sexist language
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Atribución-NoComercial-CompartirIgual 3.0 España