Free Speech, Rational Deliberation, and Some Truths About Lies

Could “fake news” have First Amendment value? This claim would seem to be almost frivolous given the potential for fake news to undermine two core functions of the freedom of speech—promoting democracy and facilitating the search for “truth,” as well as the corollary that to be valuable, speech must promote rational deliberation. Some would therefore claim that fake news should be classified as “no value” speech falling outside of the First Amendment’s reach. This Article argues somewhat counterintuitively that fake news has value because speech doctrine should not be focused exclusively on the promotion of rational deliberation, but should also limit the state’s ability to control the way we emotionally experience ideas, beliefs, and even facts. It claims that like art, music, religious expression, and other forms of human communication that do not facilitate rational deliberation in their audiences, fake news can promote a form of expressive experiential autonomy. It can allow individuals to experience individual self-realization and identity formation and also form cultural connections with like-minded people, advancing social cohesion. Drawing on First Amendment theory and on the fields of cognitive and social psychology and political science, this Article views consumers of fake news not simply as uninformed, gullible rubes, but as individuals seeking simultaneously to distinguish themselves through individualization or self-identification and to connect themselves through group association with a community of people with whom they share values. Understood in this way, this inquiry illustrates why the rational deliberation principle is incomplete because it does not explain much of what we ought to recognize as “speech.” This more nuanced understanding of the way that fake news connects with much of its audience has implications for free speech theory, First Amendment doctrine, and policy-making options for addressing the potential harms of fake news. To be clear, this Article is not a defense of fake news or those who intentionally attempt to influence others’ behavior by spreading false facts disguised as legitimate news. Thus, this Article concludes by explaining that while fake news should always be covered by the First Amendment, it should not always be protected

Combating Fake News: A Gravity Well Simulation to Model Echo Chamber Formation In Social Media

Fake news has become a serious concern as distributing misinformation has become easier and more impactful. A solution is critically required. One solution is to ban fake news, but that approach could create more problems than it solves, and would also be problematic from the beginning, as it must first be identified to be banned. We initially propose a method to automatically recognize suspected fake news, and to provide news consumers with more information as to its veracity. We suggest that fake news is comprised of two components: premises and misleading content. Fake news can be condensed down to a collection of premises, which may or may not be true, and to various forms of misleading material, including biased arguments and language, misdirection, and manipulation. Misleading content can then be exposed. While valuable, this framework’s utility may be limited by artificial intelligence, which can be used to alter fake news strategies at a rate exceeding the ability to update the framework. Therefore, we propose a model for identifying echo chambers, which are widely reported to be havens for fake news producers and consumers. We simulate a social media interest group as a gravity well, through which we identify the online groups postured to become echo chambers, and thus a source for fake news consumption and replication. This echo chamber model is supported by three pillars related to the social media group: technology employed, topic explored, and confirmation bias of group members. The model is validated by modeling and analyzing 19 subreddits on the Reddit social media platform. Contributions include a working definition for fake news, a framework for recognizing fake news, a generic model for social media echo chambers including three pillars central to echo chamber formation, and a gravity well simulation for social media groups, implemented for 19 subreddits

Fake or Credible? Towards Designing Services to Support Users’ Credibility Assessment of News Content

Fake news has become omnipresent in digitalized areas such as social media platforms. While being disseminated online, it also poses a threat to individuals and societies offline, for example, in the context of democratic elections. Research and practice have investigated the detection of fake news with behavioral science or method-related perspectives. However, to date, we lack design knowledge on presenting fake news warnings to users to support their individual news credibility assessment. We present the journey through the first design cycle on developing a fake news detection service focusing on the user interface design. The design is grounded in concepts from the field of source credibility theory and instantiated in a prototype that was qualitatively evaluated. The 13 participants communicated their interest in a lightweight application that aids in the news credibility assessment and rated the design features as useful as well as desirable

Fake News and Social Media: The Impact of Emotional Lexicon on Interactive Behaviors

As issues with fake news continue to increase, so does the need to understand better the motivation for interacting with these types of articles. Social media has become a primary source for finding news. Individuals within social media have the option to share, like, and comment on new articles. Interventions such as fake checkers, rater comments, and other types of warnings have been proven helpful in slowing the believability and interactive behaviors of fake news articles on social media sites. This qualitative, phenomenological study interviewed five participants to gain insight into how individuals experience the negative emotional lexicon within fake news articles and interact with these articles on social media. A modified Van Kaam analysis method found that the sample population does not interact (like, share, or comment) on fake news articles regardless of the language used. The study\u27s findings also found that individuals feel compelled to discuss the topic in face-to-face settings, highlighting the importance of information sharing while avoiding digital platforms as the mechanism for achieving the goal

What is fake news?

Recently, the term «fake news» has become ubiquitous in political and public discourse and the media. Despite its omnipresence, however, it is anything but clear what fake news is. An adequate and comprehensive definition of fake news is called for. We take steps towards this goal by providing a systematic account of fake news that makes the phenomenon tangible, rehabilitates the use of the term, and helps us to set fake news apart from related phenomena. (You can email us for a penultimate draft of this paper.

Diffusion of Falsehoods on Social Media

Misinformation has captured the interest of academia in recent years with several studies looking at the topic broadly. However, these studies mostly focused on rumors which are social in nature and can be either classified as false or real. In this research, we attempt to bridge the gap in the literature by examining the impacts of user characteristics and feature contents on the diffusion of (mis)information using verified true and false information. We apply a topic allocation model augmented by both supervised and unsupervised machine learning algorithms to identify tweets on novel topics. We find that retweet count is higher for fake news, novel tweets, and tweets with negative sentiment and lower lexical structure. In addition, our results show that the impacts of sentiment are opposite for fake news versus real news. We also find that tweets on the environment have a lower retweet count than the baseline religious news and real social news tweets are shared more often than fake social news. Furthermore, our studies show the counter intuitive nature of current correction endeavors by FEMA and other fact checking organizations in combating falsehoods. Specifically, we show that even though fake news causes an increase in correction messages, they influenced the propagation of falsehoods. Finally our empirical results reveal that correction messages, positive tweets and emotionally charged tweets morph faster. Furthermore, we show that tweets with positive sentiment or are emotionally charged morph faster over time. Word count and past morphing history also positively affect morphing behavior