Assisting consumers in detecting fake reviews: The role of identity information disclosure and consensus
By Andreas Munzel. 2016
149 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Information Systems, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/7e2476d8619719b5dd922d2a24ac511f2e911943
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Nripendra P. Rana
- Yogesh Kumar Dwivedi
- H. Kuo
- Emma L. Slade
- Chinintorn Nakhata
- Elvira R. Ismagilova
- Ali Abdallah Alalwan
In Information Systems
In Sociology and Political Science
- Nripendra P. Rana
- Yogesh Kumar Dwivedi
- Elvira R. Ismagilova
- Emma L. Slade
- H. Kuo
- Chinintorn Nakhata
- Marco Visentin
- Marco Pichierri
Citations in the corpus
- Fake News, Real Problems for Brands: The Impact of Content Truthfulness and Source Credibility on consumers’ Behavioral Intentions toward the Advertised Brands (2019, background): “The academic literature has analyzed deception in marketing communication (Chaouachi and Rached 2012; Craig et al. 2012; Darke and Ritchie 2007; Munzel 2016; Nelson and Park 2015; Pan and Chiou 2011), but not the particular relationship between fake news and consumers' attitudes toward an adjacent…”
- The effect of characteristics of source credibility on consumer behaviour: A meta-analysis (2020, background): “Previous research found that credibility plays an important role for valuation of eWOM message (Alalwan et al., 2017; Chang and Wu, 2014; Munzel, 2016; Teng et al., 2017; Ukpabi and Karjaluoto, 2018; Yan et al., 2018).”
- The Impact of Electronic Word-of-Mouth on Customer Satisfaction (2019, background): “Prior research has shown that consumers do not deem all eWOM to be credible and have identi fi ed several cues that help to detect fake reviews (Munzel, 2016).”