The COVID-19 Vaccine Blind Spot

According to a global survey undertaken by Ipsos, the number of people who would be vaccinated with a COVID-19 vaccine outweighs the number who wouldn't in most countries, but some European countries ranked quite low in terms of public confidence in vaccine safety (5). [...]overcoming misgivings and improving confidence in vaccination programmes are of critical importance to ensure overall success. [...]this complacency may be a result of the eradication of certain diseases, such as polio and smallpox, which could lead to forgetfulness as to how vaccines are effective tools in epidemics.

A stimulus-organism-response perspective to examine green hotel patronage intention

PurposeThis study aims to investigate the relationships among monetary cost (stimulus), perceived greenwash fear, attitude and perceived behavioural control (organism-related factors) and green hotel patronage intention (response) using the stimulus-organism-response (S-O-R) model.Design/methodology/approachA total of 262 valid questionnaires were collected. Data were collected using the purposive sampling method and tested using the partial least squares (PLS) approach.FindingsMonetary cost is positively related to only one organism-related factor which is perceived greenwash fear. All organism-related factors are positively related to response, which is green hotel patronage intention. Attitude mediates the relationship between perceived greenwash fear and green hotel patronage intention, as well as perceived behavioural control and green hotel patronage intention.Research limitations/implicationsA longitudinal study can be performed in the future to observe the actual green hotel patronage behaviour of customers.Practical implicationsGreen hoteliers should focus on the development of communication strategies to enhance their corporate reputation. Green hoteliers also need to build trust by showing their green initiatives are genuine, identify consumers who are willing to pay more for green hotels and offer promotions with price incentives such as frequency discounts, coupons and rebates to increase interest and trialability.Originality/valueFew studies have focused on the use of monetary cost as a stimulus in the S-O-R model to predict green hotel patronage intention. This study also tested the mediating effect of attitude, one of the organism-related factors, in the model.

Echoes of covid misinformation

Public support for responses to the coronavirus pandemic has sharply diverged on partisan lines in many countries, with conservatives tending to oppose lockdowns, social distancing, mask mandates and vaccines, and liberals far more supportive. This polarization may arise from the way in which the attitudes of each side is echoed back to them, especially on social media. In this paper, I argue that echo chambers are not to blame for this polarization, even if they are causally responsible for it. They are not to blame, because belief calibration in an echo chamber is a rational process;moreover, the epistemically constitutive properties of echo chambers are not optional for epistemically social animals like us. There is no special problem of echo chambers;rather, there is a problem of misleading evidence (especially higher-order evidence). Accordingly, we ought to respond to misinformation about COVID neither by attempting to dismantle echo chambers nor by attempting to make people more rational, but rather by attempting to supplant unreliable higher-order evidence with better evidence.

TwIdw—A Novel Method for Feature Extraction from Unstructured Texts

Featured ApplicationThe research has a potential application in the field of fake news detection. By using the feature extraction technique, TwIdw, proposed in this paper, more relevant and informative features can be extracted from the text data, which can lead to an enhancement in the accuracy of the classification models employed in these tasks.This research proposes a novel technique for fake news classification using natural language processing (NLP) methods. The proposed technique, TwIdw (Term weight–inverse document weight), is used for feature extraction and is based on TfIdf, with the term frequencies replaced by the depth of the words in documents. The effectiveness of the TwIdw technique is compared to another feature extraction method—basic TfIdf. Classification models were created using the random forest and feedforward neural networks, and within those, three different datasets were used. The feedforward neural network method with the KaiDMML dataset showed an increase in accuracy of up to 3.9%. The random forest method with TwIdw was not as successful as the neural network method and only showed an increase in accuracy with the KaiDMML dataset (1%). The feedforward neural network, on the other hand, showed an increase in accuracy with the TwIdw technique for all datasets. Precision and recall measures also confirmed good results, particularly for the neural network method. The TwIdw technique has the potential to be used in various NLP applications, including fake news classification and other NLP classification problems.

Is That Plausible?

Specifically, when evaluating the connections between sources of information and knowledge claims, it is important for students to reconsider the plausibility of competing claims. [...]as students work through the six steps, they are prompted to ask "Is it plausible?" when evaluating competing claims. Using this strategy, students are likely to come across information that fits into one of the following categories: misinformation, disinformation, or malinformation (see Table 2). [...]perhaps a student reads an article that falsely claims only women can contract the human papillomavirus (HPV) and states that the virus causes cervical cancer as evidence for this claim. To do this, students should check the source by asking the following questions: * Who wrote the article and where did the information first appear online? * Is the person who wrote it an expert, or did the author draw the information from expert sources? * Did the information appear on a reputable outlet? * Does the author have a financial or political motivation for making the claim that could compromise their objectivity?

An Interpretable Fake News Detection Method Based on Commonsense Knowledge Graph

Existing deep learning-based methods for detecting fake news are uninterpretable, and they do not use external knowledge related to the news. As a result, the authors of the paper propose a graph matching-based approach combined with external knowledge to detect fake news. The approach focuses on extracting commonsense knowledge from news texts through knowledge extraction, extracting background knowledge related to news content from a commonsense knowledge graph through entity extraction and entity disambiguation, using external knowledge as evidence for news identification, and interpreting the final identification results through such evidence. To achieve the identification of fake news containing commonsense errors, the algorithm uses random walks graph matching and compares the commonsense knowledge embedded in the news content with the relevant external knowledge in the commonsense knowledge graph. The news is then discriminated as true or false based on the results of the comparative analysis. From the experimental results, the method can achieve 91.07%, 85.00%, and 89.47% accuracy, precision, and recall rates, respectively, in the task of identifying fake news containing commonsense errors.

Crisis Communication during Covid–19

Early in 2020, the Covid-19 epidemic started, posing many challenges for civilisation. The pandemic caused a paradigm change in many ways, unavoidably increasing people's uncertainty and worry about a new global order. Along with stopping the virus, governments aiming to contain the pandemic had to deal appropriately with the infodemic scenario, which supported several pseudo-scientific opinions among substantial numbers of people. The spread of more and more nonsense fake news has eroded the trust in the institutions, which has led to a prolonged phase of the epidemic's end. It is yet unknown how long the coronavirus epidemic will have an impact on daily life as of the time of writing, in the summer of 2022, more outbreaks have been brought on by mask use and vaccination refusal. Because of this, controlling the crisis and reducing the harm the infodemic creates depends on effective government crisis communication. This essay attempts to illustrate effective crisis communication strategies based on international literature.

Marginalizing Misinformation - The Fast-and-Frugal Way

What is the evidence for a consensus among the relevant scientific community? [...]if the source proves credible, ask yourself, "Do they exhibit relevant expertise?" Namely, does the person have the depth of knowledge to vouch for this claim? [...]if you have a credible and expert source, is there evidence that the majority of scientists concur? (Time will vary depending on the depth and complexity of the issue.) Possible scientific claims for students to evaluate include * Do cell phones or 5G communication towers cause cancer? * Can ivermectin prevent COVID-19? * Can earthquakes be precisely predicted? * Are GMO foods safe to eat? * Are recent extreme weather events (hurricanes, droughts, floods) related to climate change? *

A puzzle of epistemic paternalism

Since the start of the Covid-19 pandemic in early 2020, conspiracy theories, misinformation, and fake news about the virus have abounded, drastically affecting global health measures to oppose it. In response, different strategies have been proposed to combat such Covid-19 collective irrationalities. One suggested approach has been that of epistemic paternalism – non-consultative interference in agents' inquiries for their epistemic improvement. While extant literature on epistemic paternalism has mainly discussed whether it is (ever) justified, in this paper, I primarily focus on the potential implementation of widespread epistemically paternalistic policies (such as no-platforming and censorship) and its consequences. I argue that pursuing epistemic paternalism to combat Covid-19 collective irrationalities leads to a hitherto unnoticed puzzle for proponents of epistemic paternalism. Central to the puzzle is the idea those (governments, corporations, social media giants) who actually can (i.e., have the requisite power to) enact widespread epistemically paternalistic policies seem the institutions who are least suited to having such informational control over the populace. Thus, epistemic paternalism appears a sword without a hilt;while it may prove an effective strategy in tackling Covid-19 collective irrationalities, we do not have any way to use it without incurring serious risks.

Journalism and COVID-19 research in Spain: academic impact, methodological approaches and disinformation

Introduction: The aim of this research is to analyze how COVID-19 was studied by the academic discipline of journalism, regarding its impact, methodology, thematic and source, and their repercussions on sites. Methodology: A universe of 124 articles is obtained through algorithmic grouping by InCites (journalism micro topic, Spanish affiliation, and COVID-19 keyword). A bibliometric analysis is performed, accompanied by a qualitative content analysis to generate common codes in methodology, themes, and use of sources. Quantitative analysis of co-occurrence and descriptive correlations between the three variables studied and their citations are carried out. Results: Articles on COVID-19 received five times more citations than the rest. The majority of cites (86%) are concentrated in the first-published articles. Classic methodologies were mostly used (49% content analysis, 16% surveys). Bibliographic review (13 cites/article) and advanced automated analysis techniques (10.75 cites/article) are the ones that receive the most citations. The main theme is disinformation (26%, 11,07 cites/article) and the most common source is the press (27%, 6,15 cites/article), although social networks (22%, 9.12 cites/article) and fact-checkers (10%, 8.50 cites/article) generated a greater impact. Discussion and Conclusions: The articles that were published during the first months generated the highest volume of citations. In journalism research, a recurrent use of classic strategies (content analysis, press) was found, although the slightly more novel approaches (advanced automated analysis techniques) are the ones that produced the most citations. Misinformation becomes one of the key issues in journalism studies. Unusual methodologies and themes receive practically no citations.Alternate :Introduction: Se analiza el impacto y el modo en el que la disciplina académica del periodismo investigó sobre el COVID-19 y su repercusión metodológica, temática y de fuentes. Metodología: Se obtiene un universo de 124 artículos mediante agrupación algorítmica por InCites (micro tópico periodismo, afiliación española y palabra clave COVID-19). Se procede a un análisis bibliométrico, acompañado por un análisis de contenido cualitativo para generar códigos comunes en metodología, temática y uso de fuentes. Se realizan análisis cuantitativos de co-ocurrencia y correlaciones descriptivas entre las tres variables estudiadas y sus citas. Resultados: Los artículos sobre COVID-19 recibieron cinco veces más citas que el resto, y la mayoría (86%) se concentran en los primeros artículos. Se emplearon mayormente metodologías clásicas (49% análisis de contenido, 16% encuestas). La revisión bibliográfica (13 citas/ artículo) y las técnicas avanzadas de análisis automático (10,75 citas/artículo) son las que reciben más citas. La temática principal es la desinformación (26%, 11,07 citas/artículo) y la fuente más común la prensa (27%, 6,15 citas/artículo), si bien generan más impacto las redes sociales (22%, 9,12 citas/ artículo) y los fact-checkers (10%, 8,50 citas/artículo). Discusión y Conclusiones: Los artículos que primero se publicaron generaron más citas. Se identificó un uso recurrente de estrategias clásicas (análisis de contenido, prensa) si bien son las aproximaciones ligeramente más novedosas (técnicas avanzadas de análisis automático) las que producen más citas. La desinformación deviene uno de los temas claves. Las metodologías y temáticas poco comunes no reciben prácticamente citaciones.

THREATS TO DEMOCRACY: CAN IT BE SUSTAINED, AND WHAT MIGHT REPLACE IT?

Democracy has increasingly come under pressure as democratic norms are being eroded. This article explores why democratic processes are at risk in Europe and the United States and what might replace them. It reflects the thinking of the Study Group on Democracy convened under the auspices of the International Association for Intelligence Education in 2022. Its deliberations identified a set of underlying key drivers, documented how they manifested, and speculated on what new forms of governance might replace democratic rule. Recent trends cited include the corruption of norms, the disruptive influence of social media, the growing diversity of society, the shift from community-based problem-solving to reliance on identity politics, the emergence of existential threats, and the need for strong leadership. The group concludes that prospects for sustaining democratic institutions can best be understood by viewing future trends along two perspectives: the complexity of society and modes of decision-making.

Pandemic Denialism: The Case of COVID-19

This article develops a typology on COVID-19 denialism so we might better understand its sources and what can be done to counter them. The typology will analyze denialism as manifested in great power competition, driven by economics and business interests, motivated by political ideology and populist movements, caused by national security imperatives, and compromised by politicized science. The article also examines the use by China and Russia of social media such as Twitter to create "epistemological chaos" in the industrialized democracies about COVID-19 to further their strategic goals and undermine public confidence in science and technology. Finally, the article concludes with some thoughts on how the social media has replaced traditional news media as a source of information for the public generally, but specifically how it has distorted the public's information about the pandemic and vaccines developed to protect against COVID.

Introduction: A Call to Engage with Denial

Cruz was appointed as head of the General Directorate of Public Health in 1903, at a time when yellow fever had killed a thousand people in the city of Rio de Janeiro alone the previous year. The newspaper printed a portrait of a man suffering from a grisly tumor in late October 1904 and claimed that vaccines caused his ailment.8 The newspaper explained that vaccines were the, "monster that pollutes the pure and innocent blood of our children with the vile excretions expelled from sick animals, of a nature that contaminates the system of any living being. "9 This newspaper article argued that it was providing the public with the "information" it needed to evaluate the government's mandates.10 It is an example of coordinated efforts to spread mis/disinformation by the press as part of the effort to create a public campaign against Alves' public health policy. Uprisings, which were also taking place in the industrial workers' neighborhoods and the Afro-Brazilian districts with fierce hand-to-hand combat, were eventually put down and citizens were pressured to retreat by the army advancing by land and the threat of bombardment by the navy docked just offshore.11 The state used repressive measures (imprisonment, beatings, interrogation, and internal exile) and put the instigators, including Senator Lauro Sodré and military officers, on trial following the uprising.12 The government declared a "state of siege" and the uprising was controlled in three days.13 However, although the government had survived the assault, the Alves administration was forced to abandon its vaccine mandate and smallpox continued to plague the country for several more years, slowing plans to modernize.

A Study on Information Disorders on Social Networks during the Chilean Social Outbreak and COVID-19 Pandemic

Information disorders on social media can have a significant impact on citizens' participation in democratic processes. To better understand the spread of false and inaccurate information online, this research analyzed data from Twitter, Facebook, and Instagram. The data were collected and verified by professional fact-checkers in Chile between October 2019 and October 2021, a period marked by political and health crises. The study found that false information spreads faster and reaches more users than true information on Twitter and Facebook. Instagram, on the other hand, seemed to be less affected by this phenomenon. False information was also more likely to be shared by users with lower reading comprehension skills. True information, on the other hand, tended to be less verbose and generate less interest among audiences. This research provides valuable insights into the characteristics of misinformation and how it spreads online. By recognizing the patterns of how false information diffuses and how users interact with it, we can identify the circumstances in which false and inaccurate messages are prone to becoming widespread. This knowledge can help us to develop strategies to counter the spread of misinformation and protect the integrity of democratic processes.

COVID-19 Infodemic in Malaysia: Conceptualizing Fake News for Detection

There is an "Infodemic” of COVID-19 in which there are a lot of rumours and information disorders spreading rapidly, the purpose of the study is to build a predictive model for identifying whether the COVID-19 information in the Malay language in Malaysia is real or fake. Under the study of COVID-19 fake news detection, the synthetic minority oversampling technique (SMOTE) is used to generate synthetic instances of real news in the training set after natural language processing (NLP) and before data modelling because the number of fake news is approximately three times greater than that of real news. Logistic regression, Naïve Bayes, decision trees, support vector machines, random forests, and gradient boosting are employed and compared to determine the most suitable predictive model. In short, the gradient-boosting classifier model has the highest value of accuracy and F1-score.

An intermestic approach to China's public diplomacy: a case study of Beijing's COVID-19 communication in the early stages

PurposeThe aim of this study was to examine the early stages of the COVID-19 outbreak and the international communication management of Chinese diplomats as a case for extending the definition of intermestic public diplomacy. The goal was to reveal how Beijing subtly used both domestic and foreign social media to organize a network for communication about COVID-19 and purposefully soften the highly centralized and hierarchical political propaganda of the Communist Party of China (CPC).Design/methodology/approachBased on the literature on digital public diplomacy, the authors applied the existing concept of intermestic to Chinese politics in order to demonstrate the digitalization of public diplomacy, along with its forms and strategies under an authoritarian regime. A hybrid methodology combining quantitative network analysis and qualitative discourse analysis permits examination of China's intermestic online communication network dynamics, shedding light on how such an intermestic practice promoted Chinese values and power to international publics in the early stages of the COVID-19 crisis.FindingsThe authors' findings extend the implications of intermestic public diplomacy from a democratic context to an authoritarian one. By analyzing the content of public diplomacy and para-diplomatic social media accounts in China and abroad at the beginning of the COVID-19 crisis, the authors outlined China's early crisis management, explaining its intermestic public diplomacy transmission modes and strategies. Moreover, the authors identified changes in the narrative strategies of Chinese diplomats and journalists during this process.Social implicationsThe findings of this study underline that Beijing established a narrative-making virtual communication structure for disseminating favorable Chinese strategic narratives and voices through differentiated communication on domestic and foreign social media platforms. Such intermestic communication strategies were particularly evident and even further weaponized by Beijing in its large-scale Wolf Warrior diplomacy in the spring of 2020. Thus, the study's findings help readers understand how China digitalized its public diplomacy, its digital communication patterns and strategies.Originality/valueOn the one hand, geopolitical uncertainty and the popularity of social media have contributed to the evolution of the intermestic model of public diplomacy. This model allows actors to coordinate homogenous and differentiated communication practices to deploy their influence. On the other hand, the authors did not examine how intermestic audiences perceive and receive public diplomacy practices. In future studies, scholars should measure the agenda-setting capacity of diplomatic actors by examining the effects of such intermestic communication efforts.

Disinformation and the Pandemic: The "Treacherous" Virus of Fake News

The pandemic represents a global emergency that has a profound impact on the lives of citizens. The contraction of spaces for personal freedom and the suspension of certain rights have altered the relationship between citizens and institutions, further modifying and weakening the dimension of the public sphere. This inherently unstable dimension is further weakened by a policy that exploits disintermediation for a construction of power based on the cancellation of the process of the acquisition of knowledge to leave space for the dynamics of polarisation and public opinion based on misinformation. The ongoing pandemic crisis represents a factor of profound destabilisation because it has exacerbated the phenomena already underway. Social distancing and physical immobility have definitively moved the construction of public discourse on the network, thus giving life to what is called platform society, where platforms produce the social structures in which we live (Van Dijck et al., 2018).