Dissemination Of Fake News Research Articles

The Internal and Extrinsic Determinants Predicting Fake News Dissemination Among Social Media Users: The Moderating Influence of Fake News Awareness.

The Internal and Extrinsic Determinants Predicting Fake News Dissemination Among Social Media Users: The Moderating Influence of Fake News Awareness.

가짜뉴스에 대한 합헌적 규제를 위한 고찰

In a technological society where macro technologies, generative artificial intelligence, and platforms have accelerated by leaps and bounds, the risks and concerns of so-called fake news are intensifying. The Internet is a forum for expression, “the most participatory medium of expression”, as Constitutional Court has affirmed. Fake news is intentionally manipulated false information that has the appearance of a journalistic article. The rapid spread of fake news through social networking services (SNS) and personal media can lead to societal and structural problems by adversely affecting the judgment of individuals, threatening the freedom of expression on the Internet, which is rooted in freedom of thought. For this reason, it is necessary to regulate the creation and dissemination of fake news on the Internet. However, regulation in response to fake news eventually leads to restrictions on freedom of expression. Against this backdrop, the constitutional issues surrounding fake news and the response to it today are clear. It is a question of balancing the public interest protected by regulating fake news against the freedom of expression restricted by doing so. Regardless of the amount of money involved, it is difficult to determine whether information is true or false, and even false information can fall under the protection of free speech and expression. For this reason, legal regulation of fake news needs to be limited to those that objectively threaten people's basic rights and the basic order of liberal democracy, and whose danger or harm is obvious and requires urgency. As the issue of the regulation of fake news has become a hot topic in Korean society, this paper reviews the existing debate from a constitutional perspective and critically examines the dangers of fake news and the need for a constitutional legislative response, especially in the current era of changing technologies and platforms. To this end, we examined the legislative bills introduced in the 20th and 21st National Assemblies from the perspectives of the constitutional principles of clarity, proportionality, and pre-censorship funding, and examined the possibilities of responding to fake news in the current legislation, suggesting social science tools and self-regulation as complements to legislative regulation.

AI Take-Over in Literature and Culture: Truth, Post-Truth, and Simulation

In a world that is increasingly lost to narrative building, deep fakes, simulation of realities and dissemination of fake news generated by artificial intelligence (AI), we are moving towards a post-truth era. Our thoughts are being manipulated and twisted with (mis)information for the benefit of people in power; thus, our consent is being manufactured with the aid of AI, resulting in ideological imperialism. In such a scenario, when AI is slowly taking control over the planet and creating our digital replicas by cloning our consciousness, what will our future look like? Humans’ creative pursuits have already predicted such futures in various movies, comics, novels and web series depicting the myriad complications associated with an impending AI takeover. Thus, contextualising today’s scenario within the scope of the future, the paper aims to dissect some popular speculative narratives offered through various tissues of culture, including movies, comics, novels and web series, to comprehend the consequences those narratives generate to grasp the changing relationalities between real and unreal, and truth and post-truth in a world run in codes and simulation.

Adam Adadelta Optimization based bidirectional encoder representations from transformers model for fake news detection on social media

Social platform have disseminated the news in rapid speed and has been considered an important news resource for many people over worldwide because of easy access and less cost benefits when compared with the traditional news organizations. Fake news is the news deliberately written by bad writers that manipulates the original contents and this rapid dissemination of fake news may mislead the people in the society. As a result, it is critical to investigate the veracity of the data leaked via social media platforms. Even so, the reliability of information reported via this platform is still doubtful and remains a significant obstacle. As a result, this study proposes a promising technique for identifying fake information in social media called Adam Adadelta Optimization based Deep Long Short-Term Memory (Deep LSTM). The tokenization operation in this case is carried out with the Bidirectional Encoder Representations from Transformers (BERT) approach. The measurement of the features is reduced with the assistance of Kernel Linear Discriminant Analysis (LDA), and Singular Value Decomposition (SVD) and the top-N attributes are chosen by employing Renyi joint entropy. Furthermore, the LSTM is applied to identify false information in social media, with Adam Adadelta Optimization, which comprises a combo of Adam Optimization and Adadelta Optimization . The Deep LSTM based on Adam Adadelta Optimization achieved maximum accuracy, sensitivity, specificity of 0.936, 0.942, and 0.925.

The Impact of Affect on the Perception of Fake News on Social Media: A Systematic Review

Social media platforms, which are ripe with emotionally charged pieces of information, are vulnerable to the dissemination of vast amounts of misinformation. Little is known about the affective processing that underlies peoples’ belief in and dissemination of fake news on social media, with the research on fake news predominantly focusing on cognitive processing aspects. This study presents a systematic review of the impact of affective constructs on the perception of fake news on social media platforms. A comprehensive literature search was conducted in the SCOPUS and Web of Science databases to identify relevant articles on the topics of affect, misinformation, disinformation, and fake news. A total of 31 empirical articles were obtained and analyzed. Seven research themes and four research gaps emerged from this review. The findings of this review complement the existing literature on the cognitive mechanisms behind how people perceive fake news on social media. This can have implications for technology platforms, governments, and citizens interested in combating infodemics.

Dissemination of fake news within transnational public spaces. Legal aspects, psychological dynamics of disinformation, and the impact of artificial intelligence

Dissemination of fake news within transnational public spaces. Legal aspects, psychological dynamics of disinformation, and the impact of artificial intelligence

Exploiting stance similarity and graph neural networks for fake news detection

The widespread dissemination of fake news on social media has substantial economic and social implications. Although traditional propagation-based methods employing graph neural networks show promise for fake news detection, they disregard the influence of confirmation bias in the spread of fake news between users with similar viewpoints. This paper presents a detection approach that accounts for opinion similarity between users by scrutinizing their stances toward news articles and users’ post interactions. Using a graph transformer network, our method simultaneously extracts global structural information and interactions of similar stances. Furthermore, it addresses the challenges of stance analysis targeting microblogs while minimizing the effect of poorly represented stance features. We evaluated our approach using custom-crawled Twitter data and the benchmark FibVID dataset. It demonstrated a marked improvement in detection performance compared with conventional methods, including state-of-the-art methods.

Fake news in business and management literature: a systematic review of definitions, theories, methods and implications

PurposeThis paper aims to conduct an interdisciplinary systematic literature review (SLR) of fake news research and to advance the socio-technical understanding of digital information practices and platforms in business and management studies.Design/methodology/approachThe paper applies a focused, SLR method to analyze articles on fake news in business and management journals from 2010 to 2020.FindingsThe paper analyzes the definition, theoretical frameworks, methods and research gaps of fake news in the business and management domains. It also identifies some promising research opportunities for future scholars.Practical implicationsThe paper offers practical implications for various stakeholders who are affected by or involved in fake news dissemination, such as brands, consumers and policymakers. It provides recommendations to cope with the challenges and risks of fake news.Social implicationsThe paper discusses the social consequences and future threats of fake news, especially in relation to social networking and social media. It calls for more awareness and responsibility from online communities to prevent and combat fake news.Originality/valueThe paper contributes to the literature on information management by showing the importance and consequences of fake news sharing for societies. It is among the frontier systematic reviews in the field that covers studies from different disciplines and focuses on business and management studies.

A comprehensive survey on machine learning approaches for fake news detection

AbstractThe proliferation of fake news on social media platforms poses significant challenges to society and individuals, leading to negative impacts. As the tactics employed by purveyors of fake news continue to evolve, there is an urgent need for automatic fake news detection (FND) to mitigate its adverse social consequences. Machine learning (ML) and deep learning (DL) techniques have emerged as promising approaches for characterising and identifying fake news content. This paper presents an extensive review of previous studies aiming to understand and combat the dissemination of fake news. The review begins by exploring the definitions of fake news proposed in the literature and delves into related terms and psychological and scientific theories that shed light on why people believe and disseminate fake news. Subsequently, advanced ML and DL techniques for FND are dicussed in detail, focusing on three main feature categories: content-based, context-based, and hybrid-based features. Additionally, the review summarises the characteristics of fake news, commonly used datasets, and the methodologies employed in existing studies. Furthermore, the review identifies the challenges current FND studies encounter and highlights areas that require further investigation in future research. By offering a comprehensive overview of the field, this survey aims to serve as a guide for researchers working on FND, providing valuable insights for developing effective FND mechanisms in the era of technological advancements.

Fake News Detection on Social Networks: A Survey

In recent years, social networks have developed rapidly and have become the main platform for the release and dissemination of fake news. The research on fake news detection has attracted extensive attention in the field of computer science. Fake news detection technology has made many breakthroughs recently, but many challenges remain. Although there are some review papers on fake news detection, a more detailed picture for carrying out a comprehensive review is presented in this paper. The concepts related to fake news detection, including fundamental theory, feature type, detection technique and detection approach, are introduced. Specifically, through extensive investigation and complex organization, a classification method for fake news detection is proposed. The datasets of fake news detection in different fields are also compared and analyzed. In addition, the tables and pictures summarized here help researchers easily grasp the full picture of fake news detection.

The challenge of infodemic: a scoping review of strategies to tackle health-related fake news

Abstract Introduction The term “infodemic” was coined by David J. Rothkopf during the SARS epidemic to describe the phenomenon of the uncontrolled spread of speculation amplified by the media and the technologies of the 21st century. During the COVID-19 pandemic, a tremendous increase of misinformation was observed. The purpose of this scoping review is to collect and describe all the strategies, tools, and recommendations available from the literature aimed at counteracting infodemic and provide useful information for decision makers to build effective responses. Methods We performed a systematic search of scientific literature from 1 January 2018 to 31 January 2023 on PubMed, Web of Science, Scopus electronic databases. Eligible articles were English article analysing tools (strategies, policies, recommendations, guidance, guidelines, toolkits, etc) aiming at supervising, monitoring, preventing and countering infodemic. Results The overall research in the scientific databases yielded a total of 5,516 record. Following the inclusion and exclusion criteria, we selected 26 articles from scientific and grey literature. From the included articles, 21 public health actions were extracted. These recommendations were grouped into five main categories (“Strategies”) that act on the infodemic phenomenon: - Increasing the health literacy of the population - Surveillance of the spread of misinformation strategies - Checking and debunking misinformation strategies - Legal and Institutional strategies - Communicate and dissemination programs Conclusions The review showed a large number of stakeholders envolved (social media companies, healthcare professionals, institutions, population). To properly address the problem of infodemia, it will be essential the creation of a solid health network, capable to tackle the spread of fake news in every moment of the process, from the surveillance systems to the checking and debunking information. Key messages • Healthcare professionals have the responsibility of disseminating information in an understandable manner; government and authorities should implement laws to tackle the dissemination of fake news. • Social media companies (and their most famous users, the ‘influencers'), should take stronger actions to contain the dissemination of fake news.

The influence of emotions on online information sharing behavior

Purpose The spread of fake news represents a serious threat to consumers, companies and society. Previous studies have linked emotional arousal to an increased propensity to spread information and a decrease in people’s ability to recognize fake news. However, the effect of an individual’s emotional state on fake news sharing remains unclear, particularly during periods of severe disruptions such as pandemics. This study aims to fill the gap in the literature by elucidating how heightened emotions affect fake news sharing behavior. Design/methodology/approach To validate the conceptual model, this study uses a quantitative approach. Data were collected from 212 online questionnaires and then analyzed using the structural equation modeling technique. Findings Results of this study show that positive emotions have indirect effects on fake news sharing behavior by allowing users to view the quality of information circulating on social media in a more positive light, and increasing their socialization behavior leading them to share fake news. Negative emotions indirectly impact fake news sharing by affecting users’ information overload and reinforcing prior beliefs, which in turn increases fake news sharing. Research limitations/implications This study identifies several novel associations between emotions and fake news sharing behavior and offers a theoretical lens that can be used in future studies. It also provides several practical implications on the prevention mechanism that can counteract the dissemination of fake news. Originality/value This study investigates the impact of individuals’ emotional states on fake news sharing behavior, and establishes four user-centric antecedents to this sharing behavior. By focusing on individuals’ emotional state, cognitive reaction and behavioral response, it is among the first, to the best of the authors’ knowledge, to offer a multidimensional understanding of individuals’ interaction with news that circulates on social media.

The relationship of artificial intelligence (AI) with fake news detection (FND): a systematic literature review

Purpose The purpose of this study is to identify the relationship between artificial intelligence (AI) and fake news detection. It also intended to explore the negative effects of fake news on society and to find out trending techniques for fake news detection. Design/methodology/approach “Preferred Reporting Items for the Systematic Review and Meta-Analysis” were applied as a research methodology for conducting the study. Twenty-five peer-reviewed, most relevant core studies were included to carry out a systematic literature review. Findings Findings illustrated that AI has a strong positive relationship with the detection of fake news. The study displayed that fake news caused emotional problems, threats to important institutions of the state and a bad impact on culture. Results of the study also revealed that big data analytics, fact-checking websites, automatic detection tools and digital literacy proved fruitful in identifying fake news. Originality/value The study offers theoretical implications for the researchers to further explore the area of AI in relation to fake news detection. It also provides managerial implications for educationists, IT experts and policymakers. This study is an important benchmark to control the generation and dissemination of fake news on social media platforms.

Modeling opinion polarization on social media: Application to Covid-19 vaccination hesitancy in Italy.

The SARS-CoV-2 pandemic reminded us how vaccination can be a divisive topic on which the public conversation is permeated by misleading claims, and thoughts tend to polarize, especially on online social networks. In this work, motivated by recent natural language processing techniques to systematically extract and quantify opinions from text messages, we present a differential framework for bivariate opinion formation dynamics that is coupled with a compartmental model for fake news dissemination. Thanks to a mean-field analysis we demonstrate that the resulting Fokker-Planck system permits to reproduce bimodal distributions of opinions as observed in polarization dynamics. The model is then applied to sentiment analysis data from social media platforms in Italy, in order to analyze the evolution of opinions about Covid-19 vaccination. We show through numerical simulations that the model is capable to describe correctly the formation of the bimodal opinion structure observed in the vaccine-hesitant dataset, which is witness of the known polarization effects that happen within closed online communities.

COVID-19 e os sistemas de saúde do Brasil e do mundo: repercussões das condições de trabalho e de saúde dos profissionais de saúde

Abstract This article discusses the impacts of the COVID-19 pandemic on health systems and its effects on the working conditions and mental health of health professionals and invisible health workers. It presents data on deaths among health professionals, highlighting the need for better and safer working conditions and improvements in public management. We emphasize WHO/PAHO recommendations and the need for equitable vaccine distribution, including poor countries and vulnerable populations. We also highlight the impacts of interrupting essential health services, such as the treatment of chronic conditions and infectious disease prevention, and the damage caused by the dissemination of fake news, stressing the need to improve access to correct and safe health information.

COVID-19 and health systems in Brazil and around the world: effects on the working conditions and health of health workers.

This article discusses the impacts of the COVID-19 pandemic on health systems and its effects on the working conditions and mental health of health professionals and invisible health workers. It presents data on deaths among health professionals, highlighting the need for better and safer working conditions and improvements in public management. We emphasize WHO/PAHO recommendations and the need for equitable vaccine distribution, including poor countries and vulnerable populations. We also highlight the impacts of interrupting essential health services, such as the treatment of chronic conditions and infectious disease prevention, and the damage caused by the dissemination of fake news, stressing the need to improve access to correct and safe health information.

The Analysis of World Information Warfare and Information Security in the Context of the Russian-Ukrainian War

The appearance of significant transnational information processes has given rise to new threats to international security, such as information warfare. The problem of employing information warfare, which has become particularly acute and relevant, can be observed through the example of the full-scale war between the Russian Federation and Ukraine. Numerous information attacks by the aggressor country in the form of fake news dissemination confirm this. The latter requires in-depth study for the development of countermeasures, the application of combat algorithms, and the organization of modern information security.This article aims to introduce a methodology of information security based on several advanced defensive administrative measures, including a review of a series of response cycles to information attacks, mainly when conducted through hybrid and information technologies in the context of the Russian-Ukrainian war. Given the rapid dynamics of contemporary information processes and associated information threats, a complex set of countermeasures is necessary enabling an effective response to threats and timely prediction.The research methodology is based on general scientific and empirical methods of analysis and scientific cognition, including observation, systemic analysis, classification, scientific abstraction, statistical analysis, analogy, graphical generalization, and systematization. According to the results of the conducted research, it has been established that the distribution of managerial decisions into "fast" and "slow" allows for combining response to attacks with information accumulation to identify the most vulnerable elements and predict future information warfare. In particular, a process of responding to information attacks consisting of several stages of administrative measures has been proposed. Attention is given to the need to consider the initial data for further use in each relevant war period when repeating the cycle following the completion of the specified four-step countermeasure algorithm. Additionally, it has been identified that transmitting data on unlawful aggressor attacks to the information collection system requires careful planning and coordination among various operations and structures. The authors have substantiated and proposed the necessity and application of coordinated administrative measures among information security entities.

To believe or not to believe: Personality, cognitive, and emotional factors involving fake news perceived accuracy

AbstractWhat are the factors that influence individuals' belief in fake news? A structured survey was conducted to examine the impact of cognitive, emotional, and personality factors on the perceived accuracy of fake news. This study utilizes certain facets of the Personality Inventory of the Diagnostic and Statistical Manual of Mental Disorders (PID‐5‐Adult trait) to investigate the phenomenon of fake news. Using actual fake news headlines encountered on Facebook, the study revealed that individuals with high levels of psychoticism, impulsivity, suspiciousness, and low analytical reasoning abilities are more likely to believe fake news. Furthermore, the study found that fear induced by news content significantly influences by impeding rational, factual analysis. These findings suggest that while social media platforms contribute to the dissemination of fake news, individual vulnerabilities also play a crucial role. These findings could be useful for the development of digital literacy programs.

Examining the Widespread Dissemination of Fake News on Facebook: Political Instability and Health Panic

The spread of fake news on Facebook is a reality. This behavior is aimed at affecting reputation and generating distrust towards a certain person or on a specific topic. A bibliometric study of the scientific production in Scopus on Fake News on Facebook in the period 2013-2023 was carried out. The results showed that fake news is promoted in political issues to generate instability and in health issues to generate confusion and panic in the population. It was concluded that citizens must develop critical thinking to question the validity of news sources. Similarly, anonymity and misinformation are a natural part of society.

Are we willing to share what we believe is true? Factors influencing susceptibility to fake news.

The contemporary media landscape is saturated with the ubiquitous presence of misinformation. One can point to several factors that amplify the spread and dissemination of false information, such as blurring the line between expert and layman's opinions, economic incentives promoting the publication of sensational information, the zero cost of sharing false information, and many more. In this study, we investigate some of the mechanisms of fake news dissemination that have eluded scientific scrutiny: the evaluation of veracity and behavioral engagement with information in light of its factual truthfulness (either true or false), cognitive utility (either enforcing or questioning participants' beliefs), and presentation style (either sober or populistic). Two main results emerge from our experiment. We find that the evaluation of veracity is mostly related to the objective truthfulness of a news item. However, the probability of engagement is more related to the congruence of the information with the participants' preconceived beliefs than to objective truthfulness or information presentation style. We conclude a common notion that the spread of fake news can be limited by fact-checking and educating people might not be entirely true, as people will share fake information as long as it reduces the entropy of their mental models of the world. We also find support for the Trojan Horse hypothesis of fake news dissemination.