潜在Dirichlet分配
情绪分析
主题模型
旅游
优势和劣势
计算机科学
数据科学
领域(数学)
社会化媒体
领域(数学分析)
人工智能
情报检索
万维网
地理
数学分析
哲学
数学
考古
认识论
纯数学
作者
Twil Ali,Omar Bencharef,Soulaimane Kaloun
出处
期刊:MethodsX
[Elsevier]
日期:2022-01-01
卷期号:9: 101894-101894
被引量:4
标识
DOI:10.1016/j.mex.2022.101894
摘要
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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