Manipulation of online reviews: An analysis of ratings, readability, and sentiments

As consumers become increasingly reliant on online reviews to make purchase decisions, the sales of the product becomes dependent on the word of mouth (WOM) that it generates. As a result, there can be attempts by firms to manipulate online reviews of products to increase their sales. Despite the su...

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Veröffentlicht in:Decision Support Systems Jg. 52; H. 3; S. 674 - 684
Hauptverfasser: Hu, Nan, Bose, Indranil, Koh, Noi Sian, Liu, Ling
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Amsterdam Elsevier B.V 01.02.2012
Elsevier
Elsevier Sequoia S.A
Schlagworte:
Applied sciences
Artificial intelligence
Assessments
Computer science; control theory; systems
Computer systems and distributed systems. User interface
Consumer behavior
Consumers
Data mining
Data processing. List processing. Character string processing
Decision support systems
Exact sciences and technology
Information systems. Data bases
Manipulation
Memory organisation. Data processing
On-line systems
Online
Online advertising
Online reviews
Outdoors
Ratings
Readability
Runs test
Sales
Sentiments
Software
Speech and sound recognition and synthesis. Linguistics
Statistical methods
Studies
Text mining
Text mining
Runs test
Readability
Sentiments
Manipulation
Online reviews
Ratings
On line
Production quality
Data mining
Legibility
Information analysis
Marketing
Sales
Consumer
Efficiency
Book
Purchases
Electronic trade
Textual data
Evaluation
Statistical analysis
Decision making
Consumer products
Social network
Text
Recommendation
ISSN:0167-9236, 1873-5797
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Zusammenfassung:As consumers become increasingly reliant on online reviews to make purchase decisions, the sales of the product becomes dependent on the word of mouth (WOM) that it generates. As a result, there can be attempts by firms to manipulate online reviews of products to increase their sales. Despite the suspicion on the existence of such manipulation, the amount of such manipulation is unknown, and deciding which reviews to believe in is largely based on the reader's discretion and intuition. Therefore, the success of the manipulation of reviews by firms in generating sales of products is unknown. In this paper, we propose a simple statistical method to detect online reviews manipulation, and assess how consumers respond to products with manipulated reviews. In particular, the writing style of reviewers is examined, and the effectiveness of manipulation through ratings, sentiments, and readability is investigated. Our analysis examines textual information available in online reviews by combining sentiment mining techniques with readability assessments. We discover that around 10.3% of the products are subject to online reviews manipulation. In spite of the deliberate use of sentiments and ratings in manipulated products, consumers are only able to detect manipulation taking place through ratings, but not through sentiments. The findings from this research ensue a note of caution for all consumers that rely on online reviews of books for making purchases, and encourage them to delve deep into the book reviews without being deceived by fraudulent manipulation. ► We examine the existence of manipulation in reviews that may mislead customers. ► We assess reviews in terms of their readability. ► We examine if reviews are manipulated through ratings and sentiments. ► We observe that reviews of 10.3% of the products in the sample are manipulated. ► Consumers are able to detect manipulation of ratings but not of sentiments.
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ISSN:0167-9236
1873-5797
DOI:10.1016/j.dss.2011.11.002