Although the influence of consumer reviews is increasing in weight, far-flung consumer comments on social networks are a retrogressive problem, disturbing users' attention in reviews studies by interpreting them as misleading messages. The need for investigating the unknown meaning layers of fake reviews in the stepwise topic movement of conversations and examining the effects of the fake reviews on consumers' shopping attitudes encouraged us to adopt an integrated approach to marketing and discourse analyses. •Qualitative analysis: To qualitatively investigate the stepwise topic movement of fake reviews in each sampled conversation of the research, three phases were taken into consideration: firstly, ; then, ; and finally, .•Quantitative investigation: we develop a questionnaire using multidisciplinary research variables. Then, the reliability and validity of the questionnaire were assessed using Cronbach's alpha and convergent and discriminant values, respectively. After that, the questionnaire was evaluated among a research sample. The data was analysed based on structural equation modeling (SEM) and machine learning (ML).•Conclusion: It was found that fake reviews using topic coherence and grammatical-lexical cohesion mechanisms had positive effects on shopping attitudes. Moreover, fake reviews using topic drift mechanisms influenced consumers' shopping attitudes.
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http://dx.doi.org/10.1016/j.mex.2023.102461 | DOI Listing |
Entropy (Basel)
November 2024
School of Economics and Management, East China Jiaotong University, Nanchang 330013, China.
In response to the widespread issue of fake comments on e-commerce platforms, this study aims to analyze and propose a blockchain-based solution to incentivize authentic user feedback and reduce the prevalence of fraudulent reviews. Specifically, this paper constructs a tripartite evolutionary game model between sellers, buyers, and e-commerce platforms to study the real comment mechanism of blockchain. The strategy evolution under different incentive factors is simulated using replication dynamic equation analysis and Matlab software simulation.
View Article and Find Full Text PDFActa Psychol (Amst)
January 2025
Research Institute of Business Analytics and Supply Chain Management, College of Management, Shenzhen University, Shenzhen, China. Electronic address:
The rise of social media has enabled unrestricted information sharing, regardless of its accuracy. Unfortunately, this has also resulted in the widespread dissemination of misinformation. This study aims to provide a comprehensive scientometric analysis under the PRISMA paradigm to clarify the repetitive trajectory of misinformation on social media in the current digital age.
View Article and Find Full Text PDFAnn Agric Environ Med
December 2024
Department of Hygiene and Dietetics, Jagiellonian University Medical College, Krakow, Poland.
Introduction And Objective: Considering the complexity of medical discourse, the enormous amount of information, including fake news, it becomes increasingly challenging to develop health literacy among the general population and to ensure efficient communication of scientific findings on the effects of health interventions to various types of recipients. We aimed to gain an in-depth understanding of how the various types of audiences perceive various formats for presenting data from Cochrane systematic reviews (SRs).
Material And Methods: We conducted focus group interviews with university employees, students, pharmacists, patients, caregivers, physicians, and nurses.
Curr Med Res Opin
December 2024
Bioethics Program, FLACSO Argentina, Buenos Aires, Argentina.
PeerJ Comput Sci
September 2024
Computer Science and Artificial Intelligence Department, College of Computer Science and Engineering, University of Jeddah, Jeddah, Saudi Arabia.
While customer reviews are crucial for businesses to maintain their standing in the marketplace, some may employ humans to create favorable reviews for their benefit. However, advances in artificial intelligence have made it less complex to create these reviews, which now rival real ones written by humans. This poses a significant challenge in distinguishing between genuine and artificially generated reviews, thereby impacting consumer trust and decision-making processes.
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