I examine the determinants and implications of false news on client business risk and firm credibility. False news is defined as information presented as factually accurate, but which contains fabricated facts and is deliberately made public to mislead the reader. Importantly, it is later denied by a credible source. There is a significant concern about the influence of false news on individuals’ decision-making and judgment processes. However, our knowledge regarding false news and its implications for financial markets is minimal. I investigate false news by focusing on negative false news that is not initiated from within the company. Building on financial and political motives behind incidents of false news, I examine whether industry competition and media coverage play a role in making a firm a target for false news. I further examine the impact of false news on the firm’s financial reporting behavior and investigate whether the firm’s auditor prices false news. Lastly, based on the argument that false news increases distrust and uncertainty, I examine whether false news decreases the credibility of the firm’s disclosures and test whether the earnings response coefficient (ERC) is lower after the release of false news. I find that lower competition and higher media coverage are associated with higher likelihood of false news. Consistent with my predictions, I also find that false news target firms have higher abnormal accruals, higher abnormal real earnings activities, and higher audit fees. However, I do not find support for the notion that false news reduces credibility of firm’s disclosure. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2019. / FAU Electronic Theses and Dissertations Collection

Vi står idag inför ett växande problem där falsk information sprids som faktaenliga nyheter i diverse olika medieformat ut till allmänheten. Detta problem kan resultera i väldiga konsekvenser på många olika sätt för både privatpersonen, den rådande politiken och samhället i stort. Denna studie är en explorativ undersökning i hur individer uppfattar falska nyheters och dess spridning samt deras tilltro till medieväsendet. Uppsatsen är en ‘’mixed methods’’ studie som bygger på en kvantitativ enkätundersökning och åtta kvalitativa intervjuer. Syftet med studien är att undersöka huruvida spridningen av falska nyheter har ökat misstron till media hos den allmänna nyhetspubliken. Studiens urvalsgrupp är 16–30 åringar då dessa är den åldersgrupp som befinner sig mest på sociala medier där den största spridningen av falska nyheter sker. Resultatet visar att det finns en allmänt stor medvetenhet om att det sker en spridning av falska nyheter. Studien visar även att denna spridning av falska nyheter har bidragit något till en ökad misstro gentemot generell nyhetsmedia. Publikens medvetenhet om falska nyheter framgår i denna undersökning klart tydligare än den uppfattade ökade misstron till nyhetskanaler, något som både den här presenterade kvantitativa och kvalitativa datan styrker. / Today we face a growing problem where false information is spread as common news out to the public. This could result in enormous consequences in many ways for people, politics and in the society as a whole. This exploratory study addresses false news and how the dissemination of these affects people and their confidence in the general news-media. The essay is a mixed method study based on a quantitative survey and eight qualitative interviews. The purpose of the study is to investigate whether the spread of false news increases the distrust of the media in the general news republic. The study's selection group are people in the ages of 16–30, as these are the age groups that most using social media where the largest spread of false news occurs. The result shows that there is an overall high awareness-rate regarding the existence of false news. The study also shows that the spread of false news has contributed to an increased mistrust towards the general news-media by the public. However, both the quantitative and qualitative data presented in this paper points to the fact that the level of awareness regarding the spreading of false news is much higher than the level of mistrust in general news outputs.

Gender-based discrimination is an issue that permeates many aspects of today's society and is influenced by numerous factors, including the presence of fake news, or emotionally driven, factually inaccurate, and misleading media. This study aimed to examine fake news' impact on consumer attitudes regarding women and to investigate how certain demographic factors relate to consumers' attitudes towards women. The current study had two main hypotheses: (1) participants exposed to fake news materials will report higher levels of both old-fashioned and modern sexism than those in other conditions and (2) participants with higher levels of sociodemographic factors such as right-wing authoritarianism (RWA) and levels of religious involvement will have higher levels of both types of sexism. Data for the current study was collected from male students at the University of Central Florida. Participants were randomly assigned to one of three experimental conditions: watching three consecutive real news clips about women, watching three consecutive fake news clips about women, or watching nothing. Participants then completed online questions related to the study's aims. Analyses conducted included correlational analyses of all variables, analysis of variance to determine if there are differences in level of sexism based on experimental condition, and linear regression analysis to determine how various sociodemographic factors relate to consumer sexism. Results indicated no significant impact of fake news on participants' levels of sexism but does demonstrate justification for future research on the topic.

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / Online social media has made the process of disseminating news so quick that people have shifted their way of accessing news from traditional journalism and press to online social media sources. The rapid rotation of news on social media makes it challenging to evaluate its reliability. Fake news not only erodes public trust but also subverts their opinions. An intelligent automated system is required to detect fake news as there is a tenuous difference between fake and real news. This paper proposes an intelligent gravitational search random forest (IGSRF) algorithm to be employed to detect fake news. The IGSRF algorithm amalgamates the Intelligent Gravitational Search Algorithm (IGSA) and the Random Forest (RF) algorithm. The IGSA is an improved intelligent variant of the classical gravitational search algorithm (GSA) that adds information about the best and worst gravitational mass agents in order to retain the exploitation ability of agents at later iterations and thus avoid the trapping of the classical GSA in local optimum. In the proposed IGSRF algorithm, all the intelligent mass agents determine the solution by generating decision trees (DT) with a random subset of attributes following the hypothesis of random forest. The mass agents generate the collection of solutions from solution space using random proportional rules. The comprehensive prediction to decide the class of news (fake or real) is determined by all the agents following the attributes of random forest. The performance of the proposed algorithm is determined for the FakeNewsNet dataset, which has sub-categories of BuzzFeed and PolitiFact news categories. To analyze the effectiveness of the proposed algorithm, the results are also evaluated with decision tree and random forest algorithms. The proposed IGSRF algorithm has attained superlative results compared to the DT, RF and state-of-the-art techniques. / Revisión por pares

This thesis revolves around the subject of fake news, a phenomenon that has been highly discussed with the advent of the internet-based media. It aims to shed light on the problem of fake news and its implications in the Turkish mainstream media by mainly departing from the discourse theory, as well as by using additional theoretical approaches over fake news and media in polarized settings. In that sense, five research questions were developed to understand how fake news items disseminate in the Turkish media ecosystem, and what this could mean for the Turkish mainstream media specifically from the contexts of political partisanship and polarization. In order to answer the research questions, a total number of 687 fake news items have been analyzed in three different data sets. After providing an overall picture of the problem of fake news in the Turkish media ecosystem, the thesis specifically focuses on fake news items that circulate within the Turkish mainstream media. Overall, 77 fake news items are further subjected to an analysis of discourse activity schema in order to find out the narratives that the fake news items are connected to the Turkish political and social context. The research shows that the use of fake news items in the Turkish mainstream media indicates divergent and conflicting epistemologies over certain social and political themes, which are government- opposition divide, secular religious divide, economy, and education. Moreover, the research also indicates that certain social and political themes are under the discursive hegemony of certain groups within the Turkish mainstream media organizations. These themes are found to be anti-immigration, anti-US, anti-Israel, and FETO. Eventually, two main points are discussed in relation to the given theoretical background. First, the problem of fake news in the Turkish mainstream media indicates a damaged understanding of journalism in the country, which requires a reorientation and reexamination. Second, media in polarized settings may increase partisan alignments and divergent epistemologies, which can lead to the use of fake news items in order to empower certain agendas.

The Swedish National Agency for Education has revised the national curriculum in order to emphasize the importance of digital competence within the Swedish public school system. One part of becoming digitally competent is to be able to critically review material from digital sources. In this study, four Swedish language upper secondary school teachers have been interviewed about their experiences in teaching digital source criticism, when a need for digital source criticism arises and how they didactically organize their teaching methods. All four informants believed that there is a need for digital source criticism although their motives and teaching methods differed. One teacher saw the use of applying the subject to democratic values, two others wanted the students to learn how to research facts and develop a more nuanced view on information, the fourth teacher wished to introduce debate and reflection. Only one of the teachers integrated digital source criticism in the teaching of the Swedish language. The other three taught it independently, as a stand-alone subject. All four teachers shared the same view on teaching digital source criticism: They need to teach the students the definition of a source and that there are different kinds of sources with a different degree of reliability.

This work focuses on the issue of fake news and related disinformation in contemporary, especially electronic media. The aim of the thesis is to clarify the definition of fake news and their function in the context of media manipulation and to give a comprehensive picture of this issue. Fake news are also related with hoaxes, rumors, urban legends, conspiracy theories and more. This work also maps the incidence of fake news especially in the Czech environment, estimates the possible reach of false news to the audience and describes their characteristics. These characteristics include captions in the form of a clickbait, highlighting emotions, manipulation with lexical means and invective, misleading or completely not specified sources (and seeming authority) and the construction of reality by image materials. Another aim of this work is to delineate the problems that fake news affect. It includes violations of journalistic ethics, growing distrust in traditional media, possible influence on political preferences, violation of legislation or personalization of the content. The research is based on the analysis of a representative sample of fake news, their comparison and a survey of public opinion. In the end, this work also proposes solutions for a defense against fake news and prevent their...

News consumption is primarily done through online news media outlets and social media. There has been a recent rise in both fake news generation, and consumption. Fake news refers to articles that deliberately contain false information to influence readers. Substantial dissemination of misinformation has been recognized to influence election results. This work focuses on hyperpartisanship in web-searched articles which refers to web searched articles which have polarized views and which represent a sensationalized view of the content. There are many such news websites which cater to propagating biased news for political and/or financial gain. This work uses Natural Language Processing (NLP) techniques on news articles to find out if a web-searched article can be termed as hyperpartisan or not. The methods were developed using a labeled dataset which was released as a part of the SemEval Task 4 - Hyperpartisan News Detection. The model was applied to queries related to U. S. midterm elections in 2018. We found that more than half the articles in web search queries showed hyperpartisanship attributes. / Master of Science / Over the recent years, the World Wide Web (WWW) has become a very important part of society. It has overgrown as a powerful medium not only to communicate with known contacts but also to gather, understand and propagate ideas with the whole world. However, in recent times there has been an increasing generation and consumption of misinformation and disinformation. These type of news, particularly fake and hyperpartisan news are particularly curated so as to hide the actual facts, and to present a biased, made-up view of the issue at hand. This activity can be harmful to the society as greater the spread and/or consumption of such news would be, more would be the negative decisions made by the readers. Thus, it poses a bigger threat to society as it affects the actions of people affected by the news. In this work, we look into a similar genre of misinformation that is hyperpartisan news. Hyperpartisan news follows a hyperpartisan orientation - the news exhibits biased opinions towards a entity (party, people, etc.) In this work, we explore to find how Natural Language Processing (NLP) methods could be used to automate the finding of hyperpartisanship in web searched articles, focusing on extraction of the linguistic features. We extend our work to test our findings in the web-searched articles related to midterm elections 2018.

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / This research addresses the dynamics that developed on the official Twitter account of Peru’s former president, Martín Vizcarra, before and during the Covid-19 pandemic. In the analysis, four trends crucial to political activity via Twitter are explored. These are the predominance of the emotional and affective component, the growing influence of fake news, deepening polarization that prevents dialogue, and the use of the platform as an information window. Results show that the pandemic effected a change in the account’s dynamics and audience participation: posting frequency on the @MartinVizcarraC account decreased, but Twitter users’ engagement more than doubled compared with the pre-pandemic period. In addition, the account strongly tended toward predominance of the emotional and affective component and informative value was the second most relevant topic for Vizcarra’s account. The communication of @MartinVizcarraC was unidirectional, focusing on the dissemination of content and avoiding conversation.

TOPICAL ANALYSIS OF FAKE NEWS 4 Abstract Since the 2016 US presidential campaign of Donald Trump, the term "fake news" has permeated mainstream discourse. The proliferation of disinformation and false narratives on social media platforms has caused concern in security circles in both the United States and European Union. Combining latent Dirichlet allocation, a machine learning method for text mining, with themes on topical analysis, ideology and social identity drawn from Critical Discourse theory, this thesis examines the elaborate fake news environments of two well-known English language websites: InfoWars and Sputnik News. Through the exploration of the ideologies and social representations at play in the larger thematic structure of these websites, a picture of two very different platforms emerges. One, a white dominant, somewhat isolationist counterculture mindset that promotes a racist and bigoted view of the world. Another, a more subtle world order-making perspective intent on reaching people in the realm of the mundane. Keywords: fake news, Sputnik, InfoWars, topical analysis, latent Dirichlet allocation Od americké prezidentské kampaně Donalda Trumpa z roku 2016, termín "fake news" (doslovně falešné zprávy) pronikl do mainstreamového diskurzu. Šíření dezinformací a falešných zpráv na platformách...