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During COVID-19, fake news on social media seriously threatened public health. As a solution to this problem, this study examined how social media exposure patterns affect people being deeply harmed by fake news. Based on cognitive dissonance theory, this study investigated the effect of intentional and incidental exposure on belief in fake news through the mediating role of confirmation bias. The results show that intentional exposure positively influences confirmation bias and belief in fake news. Incidental exposure is the opposite. Our results also show that intentional exposure and confirmation bias negatively influence incidental exposure. Furthermore, these relationships remain unchanged by gender. This study provides theoretical and empirical contributions to reducing people's belief in fake news.
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Purpose: This study aims to investigate news consumption and sharing behaviors of university students in Turkey. Method: The research was carried out on the students who are studying at the undergraduate level at foundation and state universities in Turkey. Quota sampling was used in sample selection. Data were collected by applying an online survey between June and July 2020. SPSS software was used in the analysis of the data, and descriptive statistics and chi-square test were used in the presentation of the findings. Findings: Most of the participants did not receive any training on media, news and information literacy. 93% of the participants follow the news actively, and the most preferred news sources are Twitter, online news sites and newspapers, and television. Among all news sources, the least trusted source is social media. Approximately 70% of those educated in media, news or information literacy check the source or platform of the news. Half of the participants think that journalists reflect their own prejudices on the news. In addition, the rate of those who believe that the news media is impartial is only 5%. With the onset of the coronavirus (COVID-19) pandemic, 75% of the participants started to follow the news more frequently. Implications: Findings seem to be in line with global news consumption behaviors of university students and indicate a need for a well-planned training program which specifically addresses news verification methods and techniques. Originality: The original aspect of this study is that it focuses on young people studying at universities in Turkey and deals with their news consumption and sharing behaviors.
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There are concerns with the spread of false news in recent years on news aggregator websites. In the case of Google's news aggregator service Google News, this problem is exacerbated when platform synergies are applied (for instance, users can be directed to Google News through Google's search engine, Google Search). In this article, I highlight key features of selected legislation implemented to regulate the spread of false news online and discuss their implications. I also look at the Google's efforts to self- and co-regulate, within the context of its main purposes and vulnerabilities, the mechanisms available, the monitoring of health information over the Covid-19 pandemic, as well as its commitment to codes of practices. Thereafter, I consider the limitations on regulation posed by user norms. I evaluate existing forms of regulation to assess if they are content or engagement driven, and conclude by discussing what could be more effective against disinformation for the future.
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Today, the growth of the coronavirus as a pandemic and its global expansion is a significant concern in our society and the international community. However, in recent years, many individuals have shifted their major source of news and information to social networks. Consequently, the widespread dissemination of false and misleading information on social media is significant for most politicians. Our effort is not only against COVID-19 but against an 'infodemic' as well. To address this, on COVID-19, we have collected and released a labeled dataset of 7,000 social media postings Persian data, and articles of authentic and false news. Covid 19 fake news has been detected in other languages such as Arabic, English, Chinese, and Hindi. We execute a multi-label task (actual vs. fictitious) on the labeled dataset and compare it to six machine learning baselines: Logistic Regression, Support Vector Machine, Decision Tree, Naive Bayes, K-Nearest Neighbors, and Random Forest. On the test set, the support vector machine gives us the best results, with an 89 percent accuracy rate. © 2022 IEEE.
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The rapid outbreak of COVID-19 has heightened interest in news about the pandemic. In addition to obtaining real-time developments about COVID-19, people have learned about prevention methods through the news media. Ironically, false COVID-19 news has spread faster than the virus, posing an additional health threat with advice being as dangerous as infection. In this study, we developed a Chinese news article dataset on COVID-19 misinformation, which contained 1266 verified articles from 118 Chinese digital newspaper platforms from January 2020 to January 2021. This dataset uses machine learning methods to detect false news in the Chinese language. Because automated classification methods, combined with human computation-based approaches, are effective for combating digital misinformation, we applied and evaluated a collaborative intelligence approach that leverages human fact-checking skills with feedback on news stories using four criteria: source, author, message, and spelling. The results show that reliable human feedback can help detect false news with high accuracy. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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The explosive spread of false news on social media has severely affected many areas such as news ecosystems, politics, economics, and public trust, especially amid the COVID-19 infodemic. Machine intelligence has met with limited success in detecting and curbing false news. Human knowledge and intelligence hold great potential to complement machine-based methods. Yet they are largely underexplored in current false news detection research, especially in terms of how to efficiently utilize such information. We observe that the crowd contributes to the challenging task of assessing the veracity of news by posting responses or reporting. We propose combining these two types of scalable crowd judgments with machine intelligence to tackle the false news crisis. Specifically, we design a novel framework called CAND, which first extracts relevant human and machine judgments from data sources including news features and scalable crowd intelligence. The extracted information is then aggregated by an unsupervised Bayesian aggregation model. Evaluation based on Weibo and Twitter datasets demonstrates the effectiveness of crowd intelligence and the superior performance of the proposed framework in comparison with the benchmark methods. The results also generate many valuable insights, such as the complementary value of human and machine intelligence, the possibility of using human intelligence for early detection, and the robustness of our approach to intentional manipulation. This research significantly contributes to relevant literature on false news detection and crowd intelligence. In practice, our proposed framework serves as a feasible and effective approach for false news detection. [ FROM AUTHOR] Copyright of MIS Quarterly is the property of MIS Quarterly and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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Most research on false information is currently beeing conducted in the realm of politics and Covid-19. This study addresses environmentally-related news stories. With the help of two experiments, I explore determinants that can explain who is good at distinguishing between accurate (i.e., factually correct) and false information, and compare several intervention scenarios to debunk false information. In experiment one, subjects had to rate environmentally-related news stories as accurate or false. Afterward, subjects received systematically varied information about the correctness of the news stories depending on the experimental condition they had been randomly assigned to. After a period of three weeks, the subjects were asked to evaluate the news stories again (experiment two). In experiment one, I find that the perceived familiarity with news stories increased the propensity to accept them as true. Moreover, actively open-minded thinking helped to distinguish between accurate and false information. But the willingness to think deliberately did not seem to be important. In experiment two, it can be found that by repeating false news stories, subjects were more likely to adequately identify them later (i.e., no evidence for a familiarity backfire effect). However, it decreased the likelihood to adequately identify accurate news stories. A somewhat reverse, but weaker effect occurred when factually correct news stories were repeated: the correct identification of accurate news stories was more successful, but the opposite holds for the identification of false news stories.
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El presente texto pretende realizar una fotografía de cuál es la situación actual de la verificación en Europa mediante el estudio de varios fact-checkers europeos. Con el estallido de la pandemia del coronavirus, también se ha estudiado como ha afectado esta a la labor de los verificadores. Para ello se procede a realizar un análisis de contenido de las informaciones que publican, intentando encontrar semejanzas entre las iniciativas y buscando comprender la naturaleza y características de la desinformación con la que trabajan. Además, entrevistas con profesionales de los verificadores y con especialistas en fact-checking permitirán comprender sus rutinas, metodologías, y sus estructuras empresariales, intentando de nuevo establecer convergencias en el escenario europeo. También se intentará ver como ha repercutido la crisis de desinformación causada por el coronavirus en estos medios. Al final encontramos una actividad constante y similitudes en los contenidos y metodologías. Las redes sociales (58% de los contenidos) y la política (68% de piezas) como principales vías y temáticas para la desinformación en Europa. El fact-checking como una salida factible para los periodistas, aunque no reporta grandes beneficios para las empresas. Por último, la crisis sanitaria del coronavirus ha supuesto un aumento del trabajo de estas iniciativas (en la mayoría de los casos un aumento del doble de piezas publicadas).Alternate : This text aims to take a picture of the current situation of verification in Europe by studying several European fact-checkers. With the outbreak of the coronavirus pandemic, it has also been studied how it has affected the work of verifiers. To do this, a content analysis of the information they publish is carried out, trying to find similarities between the initiatives and seeking to understand the nature and characteristics of the misinformation with which they work. In addition, interviews with professional verifiers and fact-checking specialists will allow us to understand their routines, methodologies, and business structures, trying again to establish convergences in the European scenario. An attempt will also be made to see how the disinformation crisis caused by the coronavirus has affected these media. In the end we find constant activity and similarities in the contents and methodologies. Social networks (58% of content) and politics (68% of pieces) as the main routes and themes for disinformation in Europe. Fact-checking as a feasible outlet for journalists, although it does not bring great benefits for companies. Finally, the coronavirus health crisis has led to an increase in the work of these initiatives (In most cases it has meant a double increase in published pieces).
ABSTRACT
The SARS-CoV-2 pandemic in Europe and the world has led to a number of legal, economic, medical, security and other challenges. Given the speed with which (dis) information about SARS-CoV-2 is spreading, a new term has emerged - infodemia. Infodemia is a flood of information about the virus, and it is very difficult to distinguish the truth from falsehoods. In addition, the spread of misinformation can have multiple negative consequences, both for the health of the population, mental health in particular, and the awareness of citizens about the current global situation. At the same time, infodemia can be associated with hate speech, which ultimately leads to risky behavior. Namely, such false inscriptions consequently may lead citizens into the criminal zone by disrespecting the epidemiological measures prescribed by competent authorities, which can very easily lead to global illegal action in the form of criminal offense of spreading infectious diseases. To this end, the EU seeks to respond to such undesirable and dangerous phenomena, with concrete measures that can be implemented quickly through existing legal resources. In this paper, the authors are analyzing the problem of false news spreading from criminal law and security aspects, along with comparative solutions. Namely, Croatian criminal legislation does not criminalize the dissemination of false news as a criminal offense. In our legal system the dissemination of false news is prescribed as a misdemeanor in the Misdemeanors against Public Peace and Order Act, which originated in the former state. Following the above, the authors seek to provide answers to a number of legal and security issues. First of all, what are the legal consequences of spreading false news about SARS-CoV-2, how can rumour spreading sanctions be aggravated, where are freedom of the press restrictions, and how do false information affect national security?
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Background and Objectives: The population has been overwhelmed with false information related to the Coronavirus disease (COVID-19) crisis, spreading rapidly through social media and other channels. We aimed to investigate if frontline healthcare workers affected by infodemia show different psychological consequences than frontline clinicians who do not declare to be affected by false news related to the COVID-19 pandemic. Materials and Methods: One hundred twenty-six frontline healthcare workers from the Intensive Care Unit (ICU) and Emergency Departments in Romania completed a survey to assess stress, depression, anxiety, and sleep disorders, between March and April 2020. We split the sample of frontline healthcare workers into two groups based on the self-evaluated criteria: if they were or were not affected by infodemia in their activity. Results: Considering limitations such as the cross-sectional design, the lack of causality relationship, and the sample size, the results show that, the frontline medical workers who declared to be affected by false news were significantly more stressed, felt more anxiety, and suffered more from insomnia than healthcare workers who are not affected by false information related to pandemic time. Conclusions: The infodemia has significant psychological consequences such as stress, anxiety, and insomnia on already overwhelmed doctors and nurses in the outbreak of the COVID-19 crisis. These findings suggest that medical misinformation's psychological implications must be considered when different interventions regarding frontline healthcare workers during the COVID-19 pandemic are implemented.