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Analyzing tourism reviews using an LDA topic-based sentiment analysis approach

It has become increasingly necessary to automate systems for organizing and classifying user reviews according to their domain-specific aspects and sentiment polarities, as online customer opinions have increased on specialized platforms and social networks. This study's methodology employs a c...

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Detalles Bibliográficos
Autores principales: Ali, Twil, Omar, Bencharef, Soulaimane, Kaloun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9672446/
https://www.ncbi.nlm.nih.gov/pubmed/36405368
http://dx.doi.org/10.1016/j.mex.2022.101894
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author Ali, Twil
Omar, Bencharef
Soulaimane, Kaloun
author_facet Ali, Twil
Omar, Bencharef
Soulaimane, Kaloun
author_sort Ali, Twil
collection PubMed
description It has become increasingly necessary to automate systems for organizing and classifying user reviews according to their domain-specific aspects and sentiment polarities, as online customer opinions have increased on specialized platforms and social networks. This study's methodology employs a combination of topic modeling and sentiment analysis, as well as human validation techniques of topic labels, to extract valuable insights about Marrakech city from TripAdvisor reviews. Through this technique, tourism practitioners and field specialists may dive deeper into online users generated content, leveraging aspect-based sentiment analysis to explore each destination's weaknesses and strengths. • Data collection and pre-processing. • Extracting latent topics using LDA algorithm (Latent Dirichlet Allocation) on collected reviews. • Applying sentiment analysis to each topic.
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spelling pubmed-96724462022-11-19 Analyzing tourism reviews using an LDA topic-based sentiment analysis approach Ali, Twil Omar, Bencharef Soulaimane, Kaloun MethodsX Method Article It has become increasingly necessary to automate systems for organizing and classifying user reviews according to their domain-specific aspects and sentiment polarities, as online customer opinions have increased on specialized platforms and social networks. This study's methodology employs a combination of topic modeling and sentiment analysis, as well as human validation techniques of topic labels, to extract valuable insights about Marrakech city from TripAdvisor reviews. Through this technique, tourism practitioners and field specialists may dive deeper into online users generated content, leveraging aspect-based sentiment analysis to explore each destination's weaknesses and strengths. • Data collection and pre-processing. • Extracting latent topics using LDA algorithm (Latent Dirichlet Allocation) on collected reviews. • Applying sentiment analysis to each topic. Elsevier 2022-11-05 /pmc/articles/PMC9672446/ /pubmed/36405368 http://dx.doi.org/10.1016/j.mex.2022.101894 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Method Article
Ali, Twil
Omar, Bencharef
Soulaimane, Kaloun
Analyzing tourism reviews using an LDA topic-based sentiment analysis approach
title Analyzing tourism reviews using an LDA topic-based sentiment analysis approach
title_full Analyzing tourism reviews using an LDA topic-based sentiment analysis approach
title_fullStr Analyzing tourism reviews using an LDA topic-based sentiment analysis approach
title_full_unstemmed Analyzing tourism reviews using an LDA topic-based sentiment analysis approach
title_short Analyzing tourism reviews using an LDA topic-based sentiment analysis approach
title_sort analyzing tourism reviews using an lda topic-based sentiment analysis approach
topic Method Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9672446/
https://www.ncbi.nlm.nih.gov/pubmed/36405368
http://dx.doi.org/10.1016/j.mex.2022.101894
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