Fake review detection in e-Commerce platforms using aspect-based sentiment analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F23%3A39920757" target="_blank" >RIV/00216275:25410/23:39920757 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0148296323005027" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0148296323005027</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.jbusres.2023.114143" target="_blank" >10.1016/j.jbusres.2023.114143</a>
Alternative languages
Result language
angličtina
Original language name
Fake review detection in e-Commerce platforms using aspect-based sentiment analysis
Original language description
Consumers rely on internet user reviews. Existing sentiment-based detection systems fail to capture consumer feelings regarding numerous aspects of products or services which influence their purchasing decisions. Despite the growing interest in detecting false reviews, prior studies have not explored the capacity to detect fake reviews for diverse products, which require distinct consumer experience. To overcome these problems, this paper proposes a fake review detection model using aspect-based sentiment analysis (ABSA) while considering the effects of product types. Using a dataset of Amazon reviews, our ABSA model revealed that two aspects are fundamental for detecting fake reviews and suggests the need to associate the two. These are the product category and the verified purchase attribute (with the greatest contribution observed for credence and experience product types).
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50204 - Business and management
Result continuities
Project
<a href="/en/project/GA22-22586S" target="_blank" >GA22-22586S: Aspect-based sentiment analysis of financial texts for predicting corporate financial performance</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Business Research
ISSN
0148-2963
e-ISSN
1873-7978
Volume of the periodical
167
Issue of the periodical within the volume
listopad
Country of publishing house
US - UNITED STATES
Number of pages
14
Pages from-to
114143
UT code for WoS article
001039646900001
EID of the result in the Scopus database
2-s2.0-85166630721