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Publication Detailed Description
Data and text mining from online reviews: a literature analysis
Journal Title
Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery
Year (definitive publication)
2022
Language
English
Country
United States of America
More Information
Web of Science®
Scopus
Google Scholar
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Abstract
This paper reports on a thorough analysis of the scientific literature using data and text mining to uncover knowledge from online reviews due to their importance as user-generated content. In this context, more than 12,000 papers were extracted from publications indexed in the Scopus database within the last 15 years. Regarding the type of data, most previous studies focused on qualitative textual data to perform their analysis, with fewer looking for quantitative scores and/or characterizing reviewer profiles. In terms of application domains, information management and technology, e-commerce, and tourism stand out. It is also clear that other areas of potentially valuable applications should be addressed in future research, such as arts and education, as well as more interdisciplinary approaches, namely in the spectrum of the social sciences.
Acknowledgements
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Keywords
Online reviews,Users' opinions,Consumer feedback,Data and text mining
Fields of Science and Technology Classification
- Computer and Information Sciences - Natural Sciences
Funding Records
| Funding Reference | Funding Entity |
|---|---|
| UIDB/04152/2020 | Fundação para a Ciência e a Tecnologia |
| UIDP/04466/2020 | Fundação para a Ciência e a Tecnologia |
| UIDB/04466/2020 | Fundação para a Ciência e a Tecnologia |
Related Projects
This publication is an output of the following project(s):
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