From Fake Reviews to Fake News: A Novel Pandemic Model of Misinformation in Digital Networks

Abstract

Digital networks and E-commerce platforms have had a profound effect on people’s personal, educational, and professional life all around the world. They offer space for advertising, sales, and disseminating news and information, even if they are frequently used for social marketing, interacting, and sharing thoughts among people. Currently, most E-commerce platforms utilize digital network space for advertisement and an increasing trend of social commerce is visible in all parts of the world. During the Post-COVID-19 pandemic, a rapid increase in digital media and E-commerce usage was observed in all parts of the world for personal and professional aspects. The increase in misinformation through these platforms is a major challenge that the current governments face today as rumors and fake news creates severe detrimental implications in society. In this work, we consider fake reviews and misinformation in online digital networks as a single disease, and thereby, by considering the recent trends in online social media marketing, we formulate a pandemic model for digital networks with a psychological state of human choice. The positivity and stability of the model are mathematically tested and validated. Our analysis and simulation prove that the system is stable and justifiable in the real-world digital environment. The generated pandemic model can be applied to assess the social and emotional intelligence of communities and consumers who are frequently exposed to misinformation and share fake news.

The Impact of Fake News on Traveling and Antisocial Behavior in Online Communities: Overview

“…The current knowledge collected from [44] suggests that mathematical models of pandemic propagation could be used as auxiliary models for the spread of antisocial behavior. Taking a closer look at the spread of fake news, as well as the spread of a pandemic, we can observe commonalities.…”

Modeling Rumor Spread and Influencer Impact on Social Networks

“…The suggested SEDIR (Susceptible -Exposed -Doubtful -Infected -Recovered) Model and SEDIS (Susceptible -Exposed -Doubtful -Infected -Susceptible) (see [20]) models that take into account the human nature of selection and social effect for a single viral misinformation can be considered for the study. A person is considered susceptible if they are neither infected nor immune to fake news.…”

“…The model explains the pandemic nature of fake news and misinformation in digital and social networks. This means the model considers all the misinformation, rumors, and fake news as a single disease/infection and evaluates the same (see [20]). Compared to it, the SEDIR model considers a single viral misinformation propagating through the digital network.…”

“…However, the SEDIS model allows for the potential that some users are more likely to be exposed to rumors than others based on their social network. The approach can be extended into digital networks as a pandemic model, in which disinformation is defined as a pandemic affecting digital network users [20]. Various factors influence the propagation of disinformation, including the scale of the digital network, the density of the digital network, the amount of trust between users, and the availability of interventions.…”

Leveraging Stacking Framework for Fake Review Detection in the Hospitality Sector

“…The magnitude of this predicament is starkly quantified, with the World Economic Forum estimating annual losses of an astonishing USD 152 billion due to the proliferation of counterfeit reviews, an economic loss that merits serious consideration [9]. The gravity of the problem has attracted the attention of international regulatory bodies, spanning from the European Union and the United States to Australia and India [10]. These authorities have enacted stringent measures to combat the endorsement and dissemination of counterfeit reviews.…”