Breaking news: Bericht vom Post-ASH 2003, 03.02.2004 in Köln

Fake News has been a concern all over the world and social media has only amplified this phenomenon. Fake News has been affecting the world on a large scale as these are targeted to sway the decisions of the crowd in a particular direction. Since manually verifying the legitimacy of news is very hard and costly, there has been a great interest of researchers in this field. Different approaches to identifying fake news were examined, such as content-based classification, social context-based classification, image-based classification, sentiment-based classification, and hybrid context-based classification. This paper aims to propose a model for fake news classification based on news titles, following the content-based classification approach. The model uses a BERT model with its outputs connected to an LSTM layer. Training and evaluation of the model were done on the FakeNewsNet dataset which contains two sub-datasets, PolitiFact and GossipCop. A comparison of the model with base classification models has been done. A vanilla BERT model has also been trained on the dataset under similar constraints as the proposed model has to evaluate the impact same using an LSTM layer. The results obtained showed a 2.50% and 1.10% increase in accuracy on PolitiFact and GossipCop datasets respectively over the vanilla pre-trained BERT model. 

nFake News Classification using transformer based enhanced LSTM and BERT

Background Vaccines serve an integral role in containing pandemics, yet vaccine hesitancy is prevalent globally. One key reason for this hesitancy is the pervasiveness of misinformation on social media. Although considerable research attention has been drawn to how exposure to misinformation is closely associated with vaccine hesitancy, little scholarly attention has been given to the investigation or robust theorizing of the various content themes pertaining to antivaccine misinformation about COVID-19 and the writing strategies in which these content themes are manifested. Virality of such content on social media exhibited in the form of comments, shares, and reactions has practical implications for COVID-19 vaccine hesitancy. Objective We investigated whether there were differences in the content themes and writing strategies used to disseminate antivaccine misinformation about COVID-19 and their impact on virality on social media. Methods We constructed an antivaccine misinformation database from major social media platforms during September 2019-August 2021 to examine how misinformation exhibited in the form of content themes and how these themes manifested in writing were associated with virality in terms of likes, comments, and shares. Antivaccine misinformation was retrieved from two globally leading and widely cited fake news databases, COVID Global Misinformation Dashboard and International Fact-Checking Network Corona Virus Facts Alliance Database, which aim to track and debunk COVID-19 misinformation. We primarily focused on 140 Facebook posts, since most antivaccine misinformation posts on COVID-19 were found on Facebook. We then employed quantitative content analysis to examine the content themes (ie, safety concerns, conspiracy theories, efficacy concerns) and manifestation strategies of misinformation (ie, mimicking of news and scientific reports in terms of the format and language features, use of a conversational style, use of amplification) in these posts and their association with virality of misinformation in the form of likes, comments, and shares. Results Our study revealed that safety concern was the most prominent content theme and a negative predictor of likes and shares. Regarding the writing strategies manifested in content themes, a conversational style and mimicking of news and scientific reports via the format and language features were frequently employed in COVID-19 antivaccine misinformation, with the latter being a positive predictor of likes. Conclusions This study contributes to a richer research-informed understanding of which concerns about content theme and manifestation strategy need to be countered on antivaccine misinformation circulating on social media so that accurate information on COVID-19 vaccines can be disseminated to the public, ultimately reducing vaccine hesitancy. The liking of COVID-19 antivaccine posts that employ language features to mimic news or scientific reports is perturbing since a large audience can be reached on social media, potentially exacerbating the spread of misinformation and hampering global efforts to combat the virus.

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Impact of COVID-19 Vaccine Misinformation on Social Media Virality: Content Analysis of Message Themes and Writing Strategies

Widespread misinformation about COVID-19 poses a significant threat to citizens long-term health and the combating of the disease. To fight the spread of misinformation, Chinese governments have used official social media accounts to participate in fact-checking activities. This study aims to investigate why citizens share fact-checks about COVID-19 and how to promote this activity. Based on the elaboration likelihood model, we explore the effects of peripheral cues (social media capital, social media strategy, media richness, and source credibility) and central cues (content theme and content importance) on the number of shares of fact-checks posted by official Chinese Government social media accounts. In total, 820 COVID-19 fact-checks from 413 Chinese Government Sina Weibo accounts were obtained and evaluated. Results show that both peripheral and central cues play important roles in the sharing of fact-checks. For peripheral cues, social media capital and media richness significantly promote the number of shares. Compared with the push strategy, both the pull strategy and networking strategy facilitate greater fact-check sharing. Fact-checks posted by Central Government social media accounts receive more shares than local government accounts. For central cues, content importance positively predicts the number of shares. In comparison to fact-checks about the latest COVID-19 news, government actions received fewer shares, while social conditions received more shares.

Why Do Citizens Share COVID-19 Fact-Checks Posted by Chinese Government Social Media Accounts? The Elaboration Likelihood Model.

Infodemics and Coronavirus hoaxes during the period of Covid-19 pandemic are circulating freely and massively in Indonesia. Although information widens opportunities for public to understand the dangers of Coronavirus, this raises concerns about the accuracy and clarity of existing information and pushes verified media to operate fact-checking. This content analysis reseach was conducted towards factchecking practices of 174 pandemic information published by Tempo.co, Tirto.id, and Kompas.com in March-May 2020 by elaborating fact-claims, fact-checking process, and forms of missinfodemics which leads to unnderstand that fact-checking is a complex process. First, the domination of contect fabrication and manipulation on fact-checking shows innacurate narratives on infodemics. Second, practice of fact-checking journalism is clearly addressed to verify information. Third, media have become attractive and collaborative storytellers in verifying information.

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Fact-Checking Practice Regarding Information of Covid-19 Pandemic on Tempo.co, Tirto.id, and Kompas.com

Since the World Health Organization (WHO, February 2, 2020) reported that the spread of coronavirus disease has been accompanied by a "massive infodemic," the COVID-19 outbreak has become a national and international battleground of a struggle against misinformation. Fact-checking outlets around the world have been actively counteracting false and misleading information surrounding the pandemic. In this article, we conceptualize fact checkers in terms of the "interpretative power" that journalism holds in processes of political performances (Alexander in Soc Theory 22(4): 527-573, 2004, in: The performance of politics. Obama's victory and the struggle for democratic power. Oxford University Press, Oxford/New York, 2010). Drawing on virus-related fact checks from Poynter's International Fact-Checking Network (IFCN) database, we make two arguments. First, we argue that the new phenomenon of specialized "fact checking" might be considered as a further explicitly differentiated element of Alexander's model of cultural performance, which fulfills a double duty: trying to contribute to further "de-fusion" (separating audiences from actors when the latter lack authenticity and credibility) on the one hand, and working to overcome it on the other. Second, we explain how new fact-checking practices have become a reflexive supplement to the news media of the civil sphere that might be able to help the civil sphere's communicative institutions to defend truthfulness in a manner that contributes to democracy.

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María Luengo

Papers

The performance of truth: politicians, fact-checking journalism, and the struggle to tackle COVID-19 misinformation