Comparing and evaluating tools for sentiment analysis

Sentiment analysis is a process of identifying and extracting personal information from textual data. It has become essential for businesses and organizations to understand customers' opinions, emotions, and attitudes toward their products, services, or brands. While creating a custom sentiment...

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Autores principales: Borrelli, Franco Martín, Challiol, Cecilia
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2023
Materias:
Ciencias Informáticas
Sentiment Analysis
TextBlob
Vader
Flair
HuggingFace Transformers
Ruled-based approach
Machine Learning
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/155432
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-155432
record_format dspace
spelling I19-R120-10915-1554322023-07-11T20:01:34Z http://sedici.unlp.edu.ar/handle/10915/155432 isbn:978-950-34-2271-7 Comparing and evaluating tools for sentiment analysis Borrelli, Franco Martín Challiol, Cecilia 2023-06 2023 2023-07-11T17:41:22Z en Ciencias Informáticas Sentiment Analysis TextBlob Vader Flair HuggingFace Transformers Ruled-based approach Machine Learning Sentiment analysis is a process of identifying and extracting personal information from textual data. It has become essential for businesses and organizations to understand customers' opinions, emotions, and attitudes toward their products, services, or brands. While creating a custom sentiment analysis model can provide tailored results for specific datasets, it can also be time-consuming, resource-intensive, and require a high level of expertise in machine learning. Some tools offer a faster and more accessible alternative to users without a background in machine learning to create a custom model. However, researchers and practitioners usually do not know how to choose the best tool for each domain. This paper compares and evaluates some sentiment analysis tools' differences, considering how they were built and how suitable they are for analyzing sentiments on some specific topics. In particular, this paper focuses on four popular sentiment analysis tools for Python: TextBlob, Vader, Flair, and HuggingFace Transformers. Facultad de Informática Objeto de conferencia Objeto de conferencia http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf 36-40
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Sentiment Analysis
TextBlob
Vader
Flair
HuggingFace Transformers
Ruled-based approach
Machine Learning
spellingShingle Ciencias Informáticas
Sentiment Analysis
TextBlob
Vader
Flair
HuggingFace Transformers
Ruled-based approach
Machine Learning
Borrelli, Franco Martín
Challiol, Cecilia
Comparing and evaluating tools for sentiment analysis
topic_facet Ciencias Informáticas
Sentiment Analysis
TextBlob
Vader
Flair
HuggingFace Transformers
Ruled-based approach
Machine Learning
description Sentiment analysis is a process of identifying and extracting personal information from textual data. It has become essential for businesses and organizations to understand customers' opinions, emotions, and attitudes toward their products, services, or brands. While creating a custom sentiment analysis model can provide tailored results for specific datasets, it can also be time-consuming, resource-intensive, and require a high level of expertise in machine learning. Some tools offer a faster and more accessible alternative to users without a background in machine learning to create a custom model. However, researchers and practitioners usually do not know how to choose the best tool for each domain. This paper compares and evaluates some sentiment analysis tools' differences, considering how they were built and how suitable they are for analyzing sentiments on some specific topics. In particular, this paper focuses on four popular sentiment analysis tools for Python: TextBlob, Vader, Flair, and HuggingFace Transformers.
format Objeto de conferencia
Objeto de conferencia
author Borrelli, Franco Martín
Challiol, Cecilia
author_facet Borrelli, Franco Martín
Challiol, Cecilia
author_sort Borrelli, Franco Martín
title Comparing and evaluating tools for sentiment analysis
title_short Comparing and evaluating tools for sentiment analysis
title_full Comparing and evaluating tools for sentiment analysis
title_fullStr Comparing and evaluating tools for sentiment analysis
title_full_unstemmed Comparing and evaluating tools for sentiment analysis
title_sort comparing and evaluating tools for sentiment analysis
publishDate 2023
url http://sedici.unlp.edu.ar/handle/10915/155432
work_keys_str_mv AT borrellifrancomartin comparingandevaluatingtoolsforsentimentanalysis
AT challiolcecilia comparingandevaluatingtoolsforsentimentanalysis
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