Illusions of truth—Experimental insights into human and algorithmic detections of fake online reviews

Plotkina, Daria; Munzel, Andréas; Pallud, Jessie

doi:10.1016/j.jbusres.2018.12.009

Cited by 84 publications

(72 citation statements)

References 61 publications

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“…An increasing number of fraudulent information is being spread online. Notably, this also affects online reviews [9]. So-called fake reviews are being produced and distributed from various protagonists and often deployed intentionally.…”

Section: Fake Reviews In 0e-commerce Marketingmentioning

confidence: 99%

“…Despite detailed research in the area of eWOM and online reviews, differentiated investigations of fake reviews are still rare. Most scholars focus on contributing to the identification of counterfeit reviews [9], which often implies the consideration of linguistic aspects of the review content, such as the use of specific words or phrases [18]. However, research on the causes and effects of fake reviews is fragmented.…”

Section: Fake Reviews In 0e-commerce Marketingmentioning

confidence: 99%

“…Moreover, fake reviews might impact the value of review platforms in the long run. Honest reviews could increase the quality and efficiency of the market [9], while fake reviews undermine these positive effects.…”

Section: Fake Reviews In 0e-commerce Marketingmentioning

confidence: 99%

See 2 more Smart Citations

Fake Reviews in E-Commerce Marketing

Fiedler¹,

Kissling²

2020

Herald of KNUTE

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Section: Fake Reviews In 0e-commerce Marketingmentioning

confidence: 99%

Section: Fake Reviews In 0e-commerce Marketingmentioning

confidence: 99%

See 1 more Smart Citation

Fake Reviews in E-Commerce Marketing

Fiedler¹,

Kissling²

2020

Herald of KNUTE

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“…Much like cybersecurity issues faced today, the information flow of fake news is unprecedented and at times overwhelming; mounting pressures on journalists to discern truths has allowed for both increased verification and vulnerabilities to occur in reporting. For example, fact-checking the credibility of sources is a common task, but there are many examples in mainstream media where this is not the case, and many journalists recognize the presence of this information disorder (Plotkina et al, 2020). Information excess from virtual space produces a reporting experience that can cause fact-checking to be synonymous with instantaneous discernment of sources to then act, or not act, upon.…”

Section: Introductionmentioning

confidence: 99%

Interdisciplinary Lessons Learned While Researching Fake News

et al. 2020

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The misleading and propagandistic tendencies in American news reporting have been a part of public discussion from its earliest days as a republic (Innis, 2007; Sheppard, 2007). “Fake news” is hardly new (McKernon, 1925), and the term has been applied to a variety of distinct phenomenon ranging from satire to news, which one may find disagreeable (Jankowski, 2018; Tandoc et al., 2018). However, this problem has become increasingly acute in recent years with the Macquarie Dictionary declaring “fake news” the word of the year in 2016 (Lavoipierre, 2017). The international recognition of fake news as a problem (Pomerantsev and Weiss, 2014; Applebaum and Lucas, 2016) has led to a number of initiatives to mitigate perceived causes, with varying levels of success (Flanagin and Metzger, 2014; Horne and Adali, 2017; Sample et al., 2018). The inability to create a holistic solution continues to stymie researchers and vested parties. A significant contributor to the problem is the interdisciplinary nature of digital deception. While technology enables the rapid and wide dissemination of digitally deceptive data, the design and consumption of data rely on a mixture of psychology, sociology, political science, economics, linguistics, marketing, and fine arts. The authors for this effort discuss deception’s history, both old and new, from an interdisciplinary viewpoint and then proceed to discuss how various disciplines contribute to aiding in the detection and countering of fake news narratives. A discussion of various fake news types (printed, staged events, altered photographs, and deep fakes) ensues with the various technologies being used to identify these; the shortcomings of those technologies and finally the insights offered by the other disciplines can be incorporated to improve outcomes. A three-point evaluation model that focuses on contextual data evaluation, pattern spread, and archival analysis of both the author and publication archives is introduced. While the model put forth cannot determine fact from fiction, the ability to measure distance from fact across various domains provides a starting point for evaluating the veracity of a new story.

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“…A vast literature has been developed regarding resilient or secure decision making against malicious attacks in social networks, or more generally, networked systems with interacting components [1]- [4]. Across e-commerce platforms, for example, fake online reviews from ostensible customers have caused significant damage on business [5], [6]. Security against cyber attacks has been a key issue in cyber-physical systems [7].…”

Section: Introductionmentioning

confidence: 99%

Consensus and Clustering of Expressed and Private Opinions in Dynamical Networks Against Attacks

Shang

2020

IEEE Systems Journal

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A continuous-time opinion dynamics with both expressed and private opinions on a given topic is introduced. An opinion consensus strategy is proposed to achieve resilience consensus against Byzantine attacks in dynamical networks. Necessary and sufficient criteria are established for guaranteeing consensus among normal nodes when the attacks are bounded in each neighborhood of normal nodes. A modification that allows opinion clustering, featuring non-global consensus, is presented. Numerical examples are worked out to illustrate the effectiveness of our theoretical results.

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Illusions of truth—Experimental insights into human and algorithmic detections of fake online reviews

Cited by 84 publications

References 61 publications

Fake Reviews in E-Commerce Marketing

Fake Reviews in E-Commerce Marketing

Interdisciplinary Lessons Learned While Researching Fake News

Consensus and Clustering of Expressed and Private Opinions in Dynamical Networks Against Attacks

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