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research-article

A comparative study of online consumer reviews of Apple iPhone across Amazon, Twitter and MouthShut platforms

Authors:

Supratim Kundu,

Swapnajit ChakrabortiAuthors Info & Claims

Electronic Commerce Research, Volume 22, Issue 3

Pages 925 - 950

https://doi.org/10.1007/s10660-020-09429-w

Published: 01 September 2022 Publication History

Abstract

The purpose of the paper is to understand if the online consumer reviews differ across the review platforms over the internet. We aim to find the features of the reviews from various platforms and ultimately create a typology of the reviews for those platforms. We apply mixed methods including both quantitative and qualitative techniques to arrive at the conclusion. We find consumers share their views on the highest number of topics in the ecommerce website. Consumers share in-depth views, but on a limited number of topics in other dedicated review platforms. Social media falls somewhere in the middle among these two platforms. While looking into the contents, we could generate themes and meta-themes from these reviews. Based on these facts, we create a typology/ontology for reviews from these platforms and map the motives of reviewers from each platform into the meta-themes identified. Managers can use our findings to boost their online review strategy according to the platform of their interest.

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Cited By

He PShi VZhang JChen X(2024)Channel strategy and the management of fake reviews in a catering platform service supply chainExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.122824243:COnline publication date: 25-Jun-2024
https://dl.acm.org/doi/10.1016/j.eswa.2023.122824
Lages LCatarino NGomes EToh PReis-Marques CMohr MBorde SAsgari OFigueiredo RGrosso NPerez DPonte ALopes Teixeira SVan Der Schalie RFantin DVan Brusselen JTaravat ASchmidt G(2023)Solutions for the commercialization challenges of Horizon Europe and earth observation consortia: co-creation, innovation, decision-making, tech-transfer, and sustainability actionsElectronic Commerce Research10.1007/s10660-023-09675-823:3(1621-1663)Online publication date: 6-Mar-2023
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Index Terms

A comparative study of online consumer reviews of Apple iPhone across Amazon, Twitter and MouthShut platforms

Index terms have been assigned to the content through auto-classification.

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cover image Electronic Commerce Research

Electronic Commerce Research Volume 22, Issue 3

Sep 2022

310 pages

ISSN:1389-5753

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© Springer Science+Business Media, LLC, part of Springer Nature 2020.

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Kluwer Academic Publishers

United States

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Published: 01 September 2022

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Cited By

He PShi VZhang JChen X(2024)Channel strategy and the management of fake reviews in a catering platform service supply chainExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.122824243:COnline publication date: 25-Jun-2024
https://dl.acm.org/doi/10.1016/j.eswa.2023.122824
Lages LCatarino NGomes EToh PReis-Marques CMohr MBorde SAsgari OFigueiredo RGrosso NPerez DPonte ALopes Teixeira SVan Der Schalie RFantin DVan Brusselen JTaravat ASchmidt G(2023)Solutions for the commercialization challenges of Horizon Europe and earth observation consortia: co-creation, innovation, decision-making, tech-transfer, and sustainability actionsElectronic Commerce Research10.1007/s10660-023-09675-823:3(1621-1663)Online publication date: 6-Mar-2023
https://dl.acm.org/doi/10.1007/s10660-023-09675-8
Lakshmidevi NVamsikrishna MNayak S(2022)An Optimized Deep Neural Aspect Based Framework for Sentiment ClassificationWireless Personal Communications: An International Journal10.1007/s11277-022-10081-w128:4(2953-2979)Online publication date: 10-Oct-2022
https://dl.acm.org/doi/10.1007/s11277-022-10081-w
Karn AKarna RKondamudi BBagale GPustokhin DPustokhina ISengan S(2022)RETRACTED ARTICLE: Customer centric hybrid recommendation system for E-Commerce applications by integrating hybrid sentiment analysisElectronic Commerce Research10.1007/s10660-022-09630-z23:1(279-314)Online publication date: 29-Oct-2022
https://dl.acm.org/doi/10.1007/s10660-022-09630-z

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