Spread Of Fake News Research Articles

생성형 AI가 가짜뉴스의 확산에 미치는 영향 연구

With the rapid development of generative artificial intelligence(AI) technology, concerns have been raised that it can be used to produce and disseminate fake news. Fake news is viewed as a digital organism that feeds on human interest and emotions, and how the Generative AI can increase the production and propagation power of fake news is considered. Through literature review and case analysis, the main characteristics of the Generative AI that can be abused in the production of fake news were derived. Deep learning, natural language processing, and multi-modal content synthesis are representative. Based on this, a conceptual model was proposed to explain the life cycle of AI-generated fake news and the factors of propagation within the digital platform. The research results suggest that the Generative AI can greatly amplify the scale and persuasiveness of fake news by automatically producing realistic and emotionally stimulating content. It also highlights the importance of digital platforms and user actions in the spread of AI-generated fake news. In order to cope with these threats, a multidimensional approach such as technical solutions, media literacy education, and regulation is required. An in-depth understanding of the co-evolution dynamics of AI technology and human society in the digital ecosystem is required. This study provides exploratory insights, but follow-up studies are needed for empirical verification and elaboration of the proposed model.

Fake News Detection: Traditional vs. Contemporary Machine Learning Approaches

Fake news is a growing problem in modern society. With the rise of social media and ever- increasing internet accessibility, news spreads like wildfire to millions of users in a very short time. The spread of fake news can have disastrous consequences, from decreased trust in news outlets to overturned elections. Such concerns call for automated tools to detect fake news articles. This study proposes a predictive model that can check the authenticity of a news article. The model is constructed using two different techniques to construct our model: (1) linguistic features and (2) feature extraction. We employed some widely used traditional (e.g. K-nearest neighbour (KNN) and support vector machine (SVM)) as well as state-of-the-art (e.g. bidirectional encoder representations from transformers (BERT) and extreme machine learning (ELM)) machine learning algorithms using feature extraction methods and linguistic features. After generating the models, performance metrics (e.g. accuracy and precision) are used to compare their performance. The model generated via logistic regression using feature hashing vectorisation emerged as the best model, with 99% accuracy. To the best of our knowledge, no extant studies have compared the traditional and contemporary methods in this context and demonstrated the traditional ones to be better performers. The fake news detection model can help curb the spread of fake news by acting as a tool for news organisations to check the authenticity of a news article.

Balancing Truth and Pragmatism -- Media Ethics in the Age of Fake News

In the rapid development of the information age, The goal of this paper is to explore how the media can cope with the ethical challenges when reporting news, especially the responsibility and moral dilemma when dealing with fake news and false information.By comparing and analyzing Kant s and Machiavelli s two completely different ethical views, this paper aims to explore how the media can find a balance between maintaining moral standards and practical operation in the current environment. We will discuss how the media should adhere to moral principles in the face of temptation and pressure, and explore how to effectively deal with the spread of fake news and false information in practice.

Playing an Augmented Reality Escape Game Promotes Learning About Fake News

AbstractThe spread of fake news poses a global challenge to society, as this deliberately false information reduce trust in democracy, manipulate opinions, and negatively affect people’s health. Educational research and practice must address this issue by developing and evaluating solutions to counter fake news. A promising approach in this regard is the use of game-based learning environments. In this study, we focus on Escape Fake, an augmented reality (AR) escape game developed for use in media literacy education. To date, there is limited research on the effectiveness of the game for learning about fake news. To overcome this gap, we conducted a field study using a pretest-posttest research design. A total of 28 students (14 girls, mean age = 14.71 years) participated. The results show that Escape Fake can address four learning objectives relevant in fake news detection with educationally desired effect sizes: Knowledge acquisition (d = 1.34), ability to discern information (d = 0.39), critical attitude toward trustworthiness of online information (d = 0.53), and confidence in recognizing fake news in the future (d = 0.41). Based on these results, the game can be recommended as an educational resource for media literacy education. Future research directions are also discussed.

Hoax News As An Ethical Violation Impact Of Information Technology Advances

The increasingly rapid development of technology must also be accompanied by the mindset of social network users to have harmony when facing changing times. Rephrase: Adjust the reception and dissemination of information using technology according to reality. It aims to describe the phenomenon of fake news (hoax) on social networks and online media and how to prevent fake news (hoax). It is used to visualize and describe data and facts about hoaxes and their spread through social media or online media. The study results show that easy and cheap technological advances are determining factors for information accessibility. Besides that, social media activists must also be more imaginative in utilizing information, especially an educated understanding of the media, which is often considered a source of truth, as well as the importance of the government's role in controlling the spread of fake news (hoax) that determines political decisions. Legal policies are regulated in the ITE Law.

Determinants of users' unverified information sharing on social media platforms: A herding behavior perspective

The proliferation of unverified or false information by irresponsible users can significantly amplify the spread of misinformation or fake news. Despite growing research on unverified information sharing, a comprehensive understanding of the varying influences of different factors and strategies to mitigate this issue remains under investigation. To address this research gap, this study, rooted in the theory of herd behavior, develops, and tests a model theorizing the reasons behind social media users' unverified information sharing. Data was collected from 510 respondents across six regions of China using a convenience sampling method. The collected data was analyzed using Mplus. The results from this study indicated that perceived severity, state uncertainty, and herding have a significant positive influence on unverified information sharing. These results enrich the understanding of unverified information-sharing behavior among Chinese social media users. Drawing from these results, we suggest platform administrators and policymakers mitigate herd behavior tendencies and stem the spread of misinformation by disseminating timely, accurate, and authoritative information. Since this action will reduce users' perceptions of severity and uncertainty. Social media users are also advised to stay vigilant over the implications of herd behavior and foster a more critical attitude towards information sharing.

GOVERNMANET PUBLIC RELATIONS IN FACING POLITICAL YEAR: TRAINING FOR LOCAL GOVERNMENT OF MAGETAN

The issues faced by Indonesia in the 2019 elections are likely to reemerge in the 2024 elections. In the 2019 elections, digital media became a highly effective tool for disseminating information related to politics and governance. Unfortunately, not all information available on digital media was accurate. Social media, in particular, saw a lot of misinformation and the spread of fake news (hoaxes). This led to a negative perception of the government among the public, which consequently influenced the opinions and political participation of Indonesian society. Therefore, a transformation is needed to support the formation of a positive government image. One of the strategies is maximizing government public relations. On August 8, 2023, the Communication Department at the Faculty of Social and Political Sciences, Universitas Airlangga, held a community service activity on the topic of government public relations training in Magetan Regency to address the political year. The main target of this activity was government officials in Bulukerto Subdistrict, Magetan District, Magetan Regency. The implementation mechanism consisted of three stages. In the initial stage, the community service team conducted surveys and coordinated with local government officials to gain a detailed understanding. During this stage, the Communication Department observed the involvement and performance of government public relations to obtain an initial overview of the strategies or designs used for the training. Subsequently, it was decided that the activity would be conducted through seminars and workshops covering topics such as public speaking, digital government, corporate social responsibility, and government public relations. After the activity, an evaluation was conducted to measure its success. It is hoped that this activity can serve as a foundation for improving the function of government public relations in addressing the political year and can be a supportive factor in ensuring the success of the 2024 elections.

Modeling the random spreading of fake news through a two‐dimensional time‐inhomogeneous birth‐death process

We consider a two‐dimensional time‐inhomogeneous birth‐death process to model the time‐evolution of fake news in a population. The two components of the process represent, respectively: (i) the number of individuals (say spreaders) who know the rumor and intend to spread it and (ii) the number of individuals (say inactives) who have forgotten the rumor previously received. We employ the probability generating function‐based approach to obtain the moments and the covariance of the two‐dimensional process. We also analyze a new adimensional index to study the correlation between the two components. Some special cases are considered in which both the expected numbers of spreaders and inactives are equal to suitable sigmoidal curves, which are often adopted in modeling growth phenomena. Finally, we provide an application based on real data related to the diffusion of fake news, in which the optimal choice of the sigmoidal curve that fit the datasets is based on the minimization of the mean square error and of the relative absolute error.

Fake News: “No Ban, No Spread—With Sequestration”

To curb the spread of fake news, I propose an alternative to the current trend of implementing coercive measures. This approach would preserve freedom of speech while neutralizing the social impact of fake news. The proposal relies on creating an environment to naturally sequestrate fake news within quite small networks of people. I illustrate the process using a stylized model of opinion dynamics. In particular, I explore the effect of a simultaneous activation of prejudice tie breaking and contrarian behavior, on the spread of fake news. The results show that indeed most pieces of fake news do not propagate beyond quite small groups of people and thus pose no global threat. However, some peculiar sets of parameters are found to boost fake news so that it “naturally” invades an entire community with no resistance, even if initially shared by only a handful of agents. These findings identify the modifications of the parameters required to reverse the boosting effect into a sequestration effect by an appropriate reshaping of the social geometry of the opinion dynamics landscape. Then, all fake news items become “naturally” trapped inside limited networks of people. No prohibition is required. The next significant challenge is implementing this groundbreaking scheme within social media.

Does the U.S.-China trade war stop? A novel event study on fake news and stock price in China

This study leverages the unique fake news event on the U.S.-China trade war, and adopts the difference-in-differences framework to identify its two-stage effect on stock prices in China. Our results reveal that the spread of fake news, proclaiming the end of the trade war, caused stock prices of high-tech companies to soar. After it was clarified, prices gradually decreased until the end of the first stage. But in the second stage, the stock prices of these companies grew higher than their counterparts, caused by speculation beliefs. The two-stage effect was more pronounced for the high-tech companies on the Entity List.

Pentingnya Mewujudkan Pertahanan dan Keamanan Bagi Generasi Z di Era Media Sosial

In the digital era, the spread of hoaxes poses a serious threat to national defense and security. False and misleading information can easily spread through social media, causing unrest in society and even disrupting the stability of the country. Generation Z, as active users of social media, is vulnerable to being exposed to hoaxes and is the main target for spreading them. This research aims to socialize the importance of digital literacy and strategies for dealing with hoaxes to Generation Z at SMAN 108 Jakarta. By increasing their understanding and skills in analyzing and verifying information, it is hoped that Generation Z can become the country's defense in the digital era. This research uses a descriptive qualitative method with a case study approach. Data was collected through interviews, observations and surveys of representatives of Generation Z students at SMAN 108 Jakarta. The research results show that Generation Z has sufficient understanding of digital literacy and hoaxes. They also have sufficient skills to analyze and verify information. The dissemination of digital literacy and strategies for dealing with hoaxes has proven to be effective in comprehensive information about SMAN 108 Jakarta students' understanding of the spread of hoaxes in the digital sphere. After participating in the socialization, they showed an increase in students' understanding of SMAN 108 Jakarta in using technology as wisely as possible, as well as how to deal with the spread of fake news on social media from the socialization activities that would be carried out. This research shows that disseminating digital literacy and strategies for dealing with hoaxes are important for improving national defense and security in the digital era. Generation Z needs to become smart and responsible netizens to combat the spread of hoaxes. With adequate understanding and skills, they can become agents of change and contribute to the creation of a safe and conducive digital society. It is hoped that this socialization can provide a deep understanding of the importance of handling hoaxes that spread in the digital space and become the basis for an education project for young students at SMAN 108 Jakarta as Generation Z, thereby giving birth to a generation that can think critically. With joint efforts, we can realize stronger national defense and security in the digital era.

A Multi-tier Model and Filtering Approach to Detect Fake News Using Machine Learning Algorithms

Fake news trends have overgrown in our societies over the years through social media platforms. The goal of spreading fake news can easily mislead and manipulate the public’s opinion. Many previous researchers have proposed this domain using classification algorithms or deep learning techniques. However, machine learning algorithms still suffer from high margin error, which makes them unreliable as every algorithm uses a different way of prediction. Deep learning requires high computation power and a large dataset to operate the classification model. A filtering model with a consensus layer in a multi-tier model is introduced in this research paper. The multi-tier model filters the news label correctly predicted by the first two-tier layer. The consensus layer acts as the final decision when collision results occur in the first two-tier layer. The proposed model is applied to the WEKA software tool to test and evaluate the model from both datasets. Two sequences of classification models are used in this research paper: LR_DT_RF and LR_NB_AdaBoost. The best performance of sequence for both datasets is LR_DT_RF which yields 0.9892 F1-Score, 0.9895 Accuracy, and 0.9790 Matthews Correlation Coefficient (MCC) for ISOT Fake News Dataset, and 0.9913 F1-Score, 0.9853 Accuracy, and 0.9455 MCC for CHECKED Dataset. This research could give researchers an approach for fake news detection on different social platforms and feature-based

A Review on Fake News Detection using Deep Learning Methods

The proliferation of fake news in online media platforms poses a significant threat to the integrity of information dissemination and public discourse. In response, researchers have increasingly turned to deep learning techniques to develop effective solutions for detecting and mitigating the spread of fake news. This review paper provides a comprehensive overview of recent advances in fake news detection using deep learning methodologies. We survey the literature on various deep learning architectures and approaches employed for fake news detection, including supervised, semi-supervised, and unsupervised learning methods. We discuss the challenges associated with data preprocessing, feature extraction, and model evaluation, and examine the ethical considerations and societal implications of deploying deep learning models for fake news detection. Furthermore, we identify emerging trends and future research directions in the field, with a focus on addressing the evolving nature of fake news and enhancing the robustness and interpretability of detection systems. This review contributes to the ongoing discourse on fake news detection and provides valuable insights for researchers, practitioners, and policymakers working in the domain of information integrity and online media governance.

Developing a Stressor Strain Outcome Model That Predicts Fake News Sharing Behaviour on Social Media: The Mediating Role of Social Media Exhaustion

Despite the growing corpus of knowledge on fake news sharing, nothing much is known about the relationship between the dissemination of fake news and social media exhaustion from an empirical standpoint. There is limited knowledge that exists to show if social media exhaustion could contribute to fake news-sharing behaviour. To address the gaps in the literature, this study created and evaluated a stressor strain outcome model that forecasts social media spread of fake news. It looked at the contributing elements of social media exhaustion before connecting it to disseminating fake news online. It also looked at how social media exhaustion functions as a mediator between its antecedents and fake news-sharing activity. Data was obtained from 1650 social media users using an online survey. Smart PLS structural equation modelling was used to examine the data. Our results, which drew on the stressor strain outcome model, demonstrated that, in the context of fake news-sharing behaviour, social media usage intensity is the most important predictor of social media exhaustion. Social media exhaustion was also predicted by information irrelevance, social media overload, the fear of missing out, and information overload. Also, social media tiredness predicts how people would share misleading news. Further research indicates that the link between information relevance, social overload, fear of missing out, information overload, and the dissemination of fake news is fully mediated by social media exhaustion. Conversely, it partially mediated the link between the frequency of using social media and the dissemination of false information. Our research provides recommendations to social media businesses and developers who wish to reduce concerns about social media tiredness and the spread of fake news.

Behavioral Patterns of Social Media Users toward Policy: A Scientometric Analysis

This research explores the behavioural patterns of social media users in response to policies, bridging a gap in the literature by providing in-depth insights into the interaction between user behaviour and public policies relating to social media. An important contribution of this research lies in its holistic approach to understanding how social media users respond to various public policies and their impact on their behaviour. This research aims to explore the influence of the interaction between social media and public policy, understanding how user behaviour on these platforms affects responses to government policies. This study uses qualitative research methods with a scientometric approach. The main results underline the crucial role of social media not only as a communication channel but also as a significant influence tool in shaping public opinion and policy. These studies show that social media has a dual potential, which can support professional and community development, as well as influence government policies and actions through social interaction and information dissemination. However, negative impacts are also evident, such as in the spread of fake news that can significantly alter political views. The practical implications of this research emphasise the need for proactive and systematic government strategies in using social media for the dissemination of accurate information and combating fake news, thereby improving the effectiveness of policy communication and responsiveness to public needs.

Not Only Social Networks: Channels of Dissemination of Fake News in the Views of the Population

This article presents an analysis of the problem of the spread of fake news in modern society. The dissemination of fictitious, unreliable information harms public trust, leading to uncontrollable consequences. The purpose of this work is to study the channels of media consumption and to identify the most problematic of them in the context of the spread of fake news. It is based on the results of a mass representative sociological survey of the population of the Republic of Mordovia—a typical representative of the Middle Volga region. During the research, it was found that fake news has penetrated quite firmly into the structures of everyday interaction between people: three out of ten respondents encountered fake news at least several times a month, and two out of ten shared it with others. The key channel for their distribution is social networks, internet publications, television, and Telegram channels. At the same time, these are some of the most popular sources of information. The results obtained can be useful for constructing mathematical models of the spread of fake news, developing measures to counter this kind of content, and developing mechanisms for regulating deliberately false and unreliable data.

Factors of Information Literacy Preventing Fake News: A Case Study of Libraries in Developing Countries

Factors of Information Literacy Preventing Fake News: A Case Study of Libraries in Developing Countries

Internet fraud as one of the types of fraud

The article investigates the current aspects of internet fraud in the context of the coronavirus pandemic and the Russian-Ukrainian war. The increased use of the Internet during quarantine and wartime creates new opportunities for scammers, who exploit this situation to deceive people. Emotional instability, financial problems, and the spread of misinformation also contribute to the growth of fraud online. The article analyzes the legislative approach to combating fraud in Ukraine and identifies the specifics of this type of criminal offense. Due to the accessibility of the Internet, scammers quickly adapt their schemes to the digital environment, making network users more vulnerable. The explores the diversity of methods and types of internet fraud, including phishing, cryptocurrency fraud, social engineering, and other schemes. The authors provide data from the «Data Breach and Incident Response» (DBIR) report. Methods such as phishing, farming, fraud through social media and email, as well as manipulations with ICOs and crypto investment funds, are examined in detail. Special attention is paid to fraud in wartime, mentioning fundraising for military purposes, deceptive schemes with family announcements, and fake evacuation messages. The level of vulnerability of users, geographical features, and the age category most often targeted by internet fraud are evaluated. The article also discusses the aspect of computer equipment, mobile devices, and other means of accessing the Internet used by criminals to carry out fraudulent activities. The authors emphasize the prevalence of internet fraud, where perpetrators attempt to hack websites of government organizations, banks, or media to obtain confidential information or spread fake news. Measures to combat this phenomenon are proposed. Various types of internet fraud and methods of prevention are examined in detail, including software updates, installation of antivirus software, use of strong passwords, and two- factor authentication. It is noted that awareness and a responsible approach to protection on the Internet are key to preventing fraud. Additionally, the criminal liability for fraud in Ukraine and the possibility of strengthening this liability in wartime are discussed.

Journalists and scientists together: the public problem of science disinformation in Brazil

This article analyzes the public problem of scientific disinformation in the Brazilian media covering the Covid-19 pandemic. A content analysis of 226 articles addressing disinformation as a problem was conducted in a quality newspaper (“Folha de S. Paulo”), a popular website (Metrópoles) and a science journalism magazine (“Pesquisa Fapesp”). The results suggest that the public debate has focused on spreading fake news during the Pandemic and its negative impact on public health. In addition, two opposing discourses, one populist and the other based on the scientific community and institutional normality, structured the public problem of science and disinformation in Brazil.

Role of Social Media Platforms in the Spread of Fake News in Nyeri County, Kenya

Fake news is widespread in elections, especially during presidential elections. It has the potential to divide public opinion and create a hostile environment in which people feel their voices aren't being heard. The current study aimed to explore the role of social media platforms in the spread of fake news in Nyeri County. The study is anchored in agenda-setting theory. A mixed-methods approach is used. The population comprised adults in Nyeri County, registered journalists, bloggers, and social media experts, as well as politicians in the county. A sample of 195 respondents was calculated using the modified formulas by Fisher. Questionnaires and interviews were used to collect quantitative and qualitative data, respectively. Quantitative analysis consisted of frequencies and percentages using Microsoft Excel. The qualitative data collected was analyzed using content analysis with the help of NVIVO software. The results of quantitative analysis were presented in the form of tables and figures, while those of qualitative data analysis were presented using narration. The study found that social media was the main source of fake news. Facebook and Twitter had the highest prevalence of fake news, with 87% and 72% of the respondents indicating that they witnessed fake news on the apps, respectively. The study therefore concluded that social media was the biggest source of fake news in Nyeri County. The study recommended that social media companies, especially Facebook and Twitter, should take more responsibility by implementing laws to protect against the spread of fake news. This can include flagging fake news and implementing tough penalties for users spreading propaganda on the internet.