Study of authentic and fictitious online reviews

This research investigates the ways in which differences between authentic and fictitious reviews on the Internet are related to users’ perceived review authenticity. To accomplish the goal, it addresses two research questions. The first deals with actual review authenticity while the second focuses...

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Main Author: Snehasish, Banerjee
Other Authors: Alton Chua Yeow Kuan
Format: Theses and Dissertations
Language:English
Published: 2017
Subjects:
Online Access:http://hdl.handle.net/10356/72679
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-726792020-10-28T08:52:04Z Study of authentic and fictitious online reviews Snehasish, Banerjee Alton Chua Yeow Kuan Wee Kim Wee School of Communication and Information DRNTU::Library and information science::Libraries::Information society DRNTU::Business::Marketing::Consumer behavior DRNTU::Business::Information technology::Electronic commerce DRNTU::Library and information science::Libraries::Information retrieval and analysis This research investigates the ways in which differences between authentic and fictitious reviews on the Internet are related to users’ perceived review authenticity. To accomplish the goal, it addresses two research questions. The first deals with actual review authenticity while the second focuses on humans’ perceived review authenticity. A theoretical model of authentic and fictitious reviews is developed. Guided by the model, this research examines actual differences between authentic and fictitious reviews using computational techniques. A dataset of 1,800 reviews (900 authentic + 900 fictitious) was used for investigation. Next, it examines humans’ perceived differences between authentic and fictitious reviews by surveying 380 participants. This research finds that authentic reviews are different from fictitious entries in terms of the linguistic cues of exaggeration and specificity. Moreover, humans’ perceptions of exaggeration and specificity are related to perceived authenticity. The relations tend to be particularly strong among individuals who believe that the authenticity of information cannot be justified easily. However, humans remain generally sub-par in discerning review authenticity. Overall, this research shows that even though authentic and fictitious reviews are distinguishable, human ability to discern authenticity is not overly promising. Therefore, it develops a guideline based on the actual differences between authentic and fictitious reviews to teach humans how to discern authenticity. The guideline is used as an intervention in an experimental design involving 240 participants. It is found to improve human ability to perceive differences between authentic and fictitious reviews. ​Doctor of Philosophy (WKWSCI) 2017-09-25T00:59:57Z 2017-09-25T00:59:57Z 2017 Thesis Snehasish, B. (2017). Study of authentic and fictitious online reviews. Doctoral thesis, Nanyang Technological University, Singapore. http://hdl.handle.net/10356/72679 10.32657/10356/72679 en Nanyang Technological University 254 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Library and information science::Libraries::Information society
DRNTU::Business::Marketing::Consumer behavior
DRNTU::Business::Information technology::Electronic commerce
DRNTU::Library and information science::Libraries::Information retrieval and analysis
spellingShingle DRNTU::Library and information science::Libraries::Information society
DRNTU::Business::Marketing::Consumer behavior
DRNTU::Business::Information technology::Electronic commerce
DRNTU::Library and information science::Libraries::Information retrieval and analysis
Snehasish, Banerjee
Study of authentic and fictitious online reviews
description This research investigates the ways in which differences between authentic and fictitious reviews on the Internet are related to users’ perceived review authenticity. To accomplish the goal, it addresses two research questions. The first deals with actual review authenticity while the second focuses on humans’ perceived review authenticity. A theoretical model of authentic and fictitious reviews is developed. Guided by the model, this research examines actual differences between authentic and fictitious reviews using computational techniques. A dataset of 1,800 reviews (900 authentic + 900 fictitious) was used for investigation. Next, it examines humans’ perceived differences between authentic and fictitious reviews by surveying 380 participants. This research finds that authentic reviews are different from fictitious entries in terms of the linguistic cues of exaggeration and specificity. Moreover, humans’ perceptions of exaggeration and specificity are related to perceived authenticity. The relations tend to be particularly strong among individuals who believe that the authenticity of information cannot be justified easily. However, humans remain generally sub-par in discerning review authenticity. Overall, this research shows that even though authentic and fictitious reviews are distinguishable, human ability to discern authenticity is not overly promising. Therefore, it develops a guideline based on the actual differences between authentic and fictitious reviews to teach humans how to discern authenticity. The guideline is used as an intervention in an experimental design involving 240 participants. It is found to improve human ability to perceive differences between authentic and fictitious reviews.
author2 Alton Chua Yeow Kuan
author_facet Alton Chua Yeow Kuan
Snehasish, Banerjee
format Theses and Dissertations
author Snehasish, Banerjee
author_sort Snehasish, Banerjee
title Study of authentic and fictitious online reviews
title_short Study of authentic and fictitious online reviews
title_full Study of authentic and fictitious online reviews
title_fullStr Study of authentic and fictitious online reviews
title_full_unstemmed Study of authentic and fictitious online reviews
title_sort study of authentic and fictitious online reviews
publishDate 2017
url http://hdl.handle.net/10356/72679
_version_ 1683493506043084800