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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
Descripción
Sumario: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.