Classification of Covid-19 misinformation on social media based on neuro-fuzzy and neural network: A systematic review

Abstract

The spread of Covid-19 misinformation on social media had significant real-world consequences, and it raised fears among internet users since the pandemic has begun. Researchers from all over the world have shown an interest in developing deception classification methods to reduce the issue. Despite numerous obstacles that can thwart the efforts, the researchers aim to create an automated, stable, accurate, and effective mechanism for misinformation classification. In this paper, a systematic literature review is conducted to analyse the state-of-the-art related to the classification of misinformation on social media. IEEE Xplore, SpringerLink, ScienceDirect, Scopus, Taylor & Francis, Wiley, Google Scholar are used as databases to find relevant papers since 2018–2021. Firstly, the study begins by reviewing the history of the issues surrounding Covid-19 misinformation and its effects on social media users. Secondly, various neuro-fuzzy and neural network classification methods are identified. Thirdly, the strength, limitations, and challenges of neuro-fuzzy and neural network approaches are verified for the classification misinformation specially in case of Covid-19. Finally, the most efficient hybrid method of neuro-fuzzy and neural networks in terms of performance accuracy is discovered. This study is wrapped up by suggesting a hybrid ANFIS-DNN model for improving Covid-19 misinformation classification. The results of this study can be served as a roadmap for future research on misinformation classification.

Quantitative analysis of social media use in the energy and resources sector: national comparison and sector analysis

“…As most companies in the energy and resources sector deal with B2B companies, social media platforms are predominantly used for community engagement, with the primary goal of creating a reputable brand image in the primary market (Khan et al, 2014;Ravichandran and Keikhosrokiani, 2023). However, this has only been the case since the 2000s, when the first social media platforms were being developed (Mergel, 2013).…”

“…The choice of a preferred social media platform by a company is commonly determined by its desired objectives, with a preference for a platform that will achieve the best results in community engagement (Lampe and Roth, 2012;Ravichandran and Keikhosrokiani, 2023). In each case, the principles of environmental, social, and governance (ESG) and SLO are observed; a social media platform that enables firms to achieve these objectives is preferred.…”

An Accurate Disease Classification of COVID-19 and Pneumonia from Chest X-Ray Images Utilizing Mathematical Algorithm-Based Deep Learning Model

“…However, due to the significant similarities between COVID-19, viral pneumonia, and tuberculosis, it presents a challenge for physicians to distinguish between them solely based on chest X-rays [7][8][9]. Numerous research studies have been conducted to classify cases as either COVID-19 or healthy [10], COVID-19 or pneumonia [11], or COVID-19 or Tuberculosis (TB) [12]. However, these studies lacked the ability to accurately make a clear distinction between these diseases using chest X-rays.…”

The moderating influence of perceived government information transparency on COVID-19 pandemic information adoption on social media systems

“…Furthermore, social media systems have been used by new agencies, organizations, and society to share information and disinformation about the pandemic ( Ravichandran and Keikhosrokiani, 2023 ). Misinformation entails information that is incorrect but not intended to deceive or cause harm while disinformation is false information that is intentionally created to harm a person, social group, organization, or country and it is often motivated by financial or political purposes ( Gisondi et al, 2022 ).…”

“…Terms such as fake news, rumors, conspiracy theories, false information misleading information, are often connected to the misinformation paradigm ( Sanaullah et al, 2022 ). People’s behavior (unhealthy health behaviors and unsound practices) which is based on the accuracy or inaccuracy of the information are crucial to the global management health response to the pandemic ( Sanaullah et al, 2022 ; Ravichandran and Keikhosrokiani, 2023 ). This is buttressed by reports indicating that COVID-19 misinformation presents a huge risk to public health and public action to fight the unprecedented nature of the COVID-19 pandemic ( Barua et al, 2020 ; Bridgman et al, 2020 ).…”