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The COVID-19 pandemic has disproportionately impacted health and social outcomes for people of color in the United States. This study examined how local TV news stories attributed causes and solutions for COVID-19-related racial health and social disparities, and whether coverage of such disparities changed after George Floyd's murder, during the first wave of the COVID-19 pandemic. We systematically validated keywords to extract relevant news content and conducted a content analysis of 169 discrete local TV news stories aired between March and June 2020 from 80 broadcast networks within 22 purposefully selected media markets. We found that social determinants of COVID-19 related racial disparities have been part of the discussion in local TV news, but racism as a public health crisis was rarely mentioned. Coverage of racial disparities focused far more attention on physical health outcomes than broader social impacts. Stories cited more structural factors than individual factors, as causes of these disparities. After the murder of George Floyd, stories were more likely to mention Black and Latinx people than other populations impacted by COVID-19. Only 9% of local news stories referenced racism, and stories referenced politicians more frequently than public health experts., Competing Interests: Conflict of interestThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© The Author(s) 2022.)

This study explores the factors that influence the dissemination process of and public susceptibility to fake news amidst COVID-19. By adopting a qualitative approach that draws on 21 interviews with social media users from the standpoint of source credibility and construal level theories, our findings highlight motives of news sharers, platform features, and source credibility/relatedness as major factors influencing the dissemination of and public susceptibility to fake news. The paper further argues that public susceptibility to fake news can be mitigated by building an integrated approach that combines a tripartite strategy from an individual, institutional and platform level. For example, educating the public on digital resilience and enhancing awareness around source credibility can help individuals and institutions reflect on news authenticity and report fake news where possible. This study contributes to fake news literature by integrating concepts from information management, consumer behaviour, influencer marketing and mindfulness to propose a model to help authorities identify and understand the key factors that influence susceptibility to fake news during a public crisis such as COVID-19., Competing Interests: Conflicts of InterestAuthors have no conflict of interests to declare., (© The Author(s) 2022.)

Event detection from textual content by using text mining concepts is a well-researched field in the literature. On the other hand, graph modeling and graph embedding techniques in recent years provide an opportunity to represent textual contents as graphs. Text can be enriched with additional attributes in graphs, and the complex relationships can be captured within the graphs. In this paper, we focus on news prediction and model the problem as subgraph prediction. More specifically, we aim to predict the news skeleton in the form of a subgraph. To this aim, graph-based representations of news articles are constructed and a graph mining based pattern extraction method is proposed. The proposed method consists of three main steps. Initially, graph representation of the news text is constructed. Afterwards, frequent subgraph mining and sequential rule mining algorithms are adapted for pattern prediction on graph sequences. We consider that a subgraph captures the main story of the contents, and the sequential rules indicate the subgraph patterns' temporal relationships. Finally, extracted sequential patterns are used for predicting the future news skeleton (i.e. main features of the news). In order to measure the similarity, graph embedding techniques are also employed. The proposed method is analyzed on both a collection of news from an online newspaper and on a benchmark news dataset against baseline methods., Competing Interests: Conflict of InterestsThe authors declare that they have no conflict of interest., (© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022.)

We study the impact of new information on people's perceptions of the risks of e-cigarettes. In September 2019 the U.S. experienced an outbreak of e-cigarette, or vaping, associated lung injuries (EVALI). The EVALI outbreak created an information shock, which was followed by additional new information in a later CDC recommendation. We use data on consumer risk perceptions from two sets of surveys conducted before (HINTS survey data) and during the EVALI outbreak (Google Survey data). The empirical model examines changes in risk perceptions during the early crisis period when the CDC was warning consumers that they should avoid all vaping products and during a later period when the message was refined and focused on a narrower set of illegal vaping products that contain THC (the main psychoactive compound in marijuana). Econometric results suggest that the immediate impact of the first information shock was to significantly increase the fraction of respondents who perceived e-cigarettes as more harmful than smoking. As the outbreak subsided and the CDC recommendation changed to emphasize the role of THC e-cigarette products, e-cigarette risk perceptions were only partially revised downwards. Individuals who had higher risk perceptions showed a weaker response to the first information shock but were more likely to later revise their risk perceptions downwards. We conclude the paper by discussing the public policy issues that stem from having risk perceptions of e-cigarette relative to combustible cigarettes remain at these elevated levels where a substantial portion of consumers believe that e-cigarettes are more harmful than cigarettes.