Tag: Climate Change Disinformation

Abstract

Background

The COVID-19 pandemic initiated a great global crisis, during which media influenced society and social interactions affected media use. Researchers from various research fields have studied the pandemic both globally and locally. This study aims to summarize the research on COVID-19 pandemic within communication studies, taking into account 358 articles published in SJR best ranked journals in 2020–2022.

Methods

The study uses both qualitative and quantitative methods. Using manual coding and qualitative content analysis, we investigate articles’ distribution according to journals, time, accessibility (either open, free or restricted) and methodological approaches. We also provide a qualitative summary of trending research themes. Using quantitative social network analysis (SNA) we present the distribution of institutions and countries in articles’ affiliations, and the collaboration network at institutional and country level.

Results

Results show an in-time increase of COVID-related publications. Articles were affiliated with 490 institutions from 68 countries, with the USA having the greatest representation. There was an underrepresentation of African and South American countries, which reflects the core-periphery challenge in knowledge production. The network analysis revealed that very few of possible connections were actually achieved. There is an observable trend of using quantitative methods. A growth on the gap between qualitative and quantitative studies was observed each year. More than a half of articles using qualitative methods were published in restricted access. Our qualitative summary of the addressed topics and main findings in articles related to COVID-19, media and society revealed a wide research interest in pandemics impacts on news consumption, media use and journalism, as well as infodemic, conspiracy narratives, science mistrust and discrimination and inequalities increased by the pandemic.

Conclusion

To provide a wider perspective on the worldwide impact of pandemic, more studies from underrepresented countries are needed. The collaboration between institutions and countries requires strengthening. Qualitative studies were conducted considerably less than quantitative studies and they were usually published in restricted access, which leads to a methodological gap.

Recent advances in artificial intelligence (AI) have introduced transformative capabilities that are revolutionizing the process of scientific research and communication. AI tools can assist researchers in designing studies, analyzing data, and drafting manuscripts, enhancing both efficiency and analytical rigor. This allows researchers to focus cognitive resources on higher-level conceptualization and interpretation. Furthermore, AI holds promise for steering research towards more impactful directions by aiding in the identification of critical knowledge gaps and research questions with potential societal benefits. Collaboration platforms powered by AI facilitate connections between researchers across domains and institutions, accelerating discovery and promoting convergence around global health priorities. However, responsible development and application of AI in research is essential. Transparency, explainability, data privacy, and human oversight must remain priorities to ensure ethical AI practices. While AI offers transformative capabilities, researchers must maintain agency and responsibility over the scientific process. With thoughtful governance and participatory design, AI can become a powerful tool for advancing science in the service of society. Overall, AI ushers in new potentials for improving the rigor, relevance, and reach of scientific inquiry. Yet realization of this potential necessitates proactive efforts to address emerging risks and challenges.

Abstract

Mis- and disinformation pose substantial societal challenges, and have thus become the focus of a substantive field of research. However, the field of misinformation research has recently come under scrutiny on two fronts. First, a political response has emerged, claiming that misinformation research aims to censor conservative voices. Second, some scholars have questioned the utility of misinformation research altogether, arguing that misinformation is not sufficiently identifiable or widespread to warrant much concern or action. Here, we rebut these claims. We contend that the spread of misinformation—and in particular willful disinformation—is demonstrably harmful to public health, evidence-informed policymaking, and democratic processes. We also show that disinformation and outright lies can often be identified and differ from good-faith political contestation. We conclude by showing how misinformation and disinformation can be at least partially mitigated using a variety of empirically validated, rights-preserving methods that do not involve censorship.

Abstract

This survey paper explores the transformative role of Artificial Intelligence (AI) in information security. Traditional methods, especially rule-based approaches, faced significant challenges in protecting sensitive data from ever-changing cyber threats, particularly with the rapid increase in data volume. This study thoroughly evaluates AI’s application in information security, discussing its strengths and weaknesses. It provides a detailed review of AI’s impact on information security, examining various AI algorithms used in this field, such as supervised, unsupervised, and reinforcement learning, and highlighting their respective strengths and limitations. The study identifies key areas for future AI research in information security, focusing on improving algorithms, strengthening information security, addressing ethical issues, and exploring safety and security-related concerns. It emphasizes significant security risks, including vulnerability to adversarial attacks, and aims to enhance the robustness and reliability of AI systems in protecting sensitive information by proposing solutions for potential threats. The findings aim to benefit cybersecurity professionals and researchers by offering insights into the intricate relationship between AI, information security, and emerging technologies.

Abstract

Increasing the willingness to reduce animal product consumption has the potential to contribute to ameliorating the impact of animal agriculture on the environment, as well as foster healthier diets and improve the lives of farmed and wild animals. Reduction of animal product consumption is a prosocial behaviour (PSB), and factors that are considered to influence it are empathy and selfishness. In this research, animal-oriented empathy examined empathy specifically for animals. Animal oriented empathy and three types of selfishness: adaptive, egoistic, and pathological were measured to determine if they could predict willingness to reduce animal product consumption. PSB is also influenced by motivations and motivations can lead to willingness. The three most common motivations to reduce animal product consumption: animal welfare, the environment, and health were examined to determine whether they predict willingness. A sample of 492 Australian adults completed questionnaires via the Zoho survey platform, and the data underwent a hierarchical regression. Higher pathological selfishness predicted a greater willingness to reduce animal product consumption, as did environmental and animal welfare motivations. However, higher health motivation predicted a lower willingness to reduce animal product consumption. Interpretation of the perplexing results in relation to pathological selfishness suggested further research. The practical value of utilising environmental and animal motivations to increase willingness to reduce animal products whilst bringing attention to the health issues was also discussed.

Abstract

Hate speech psychologically harms its targeted people. It sometimes leads to hate crimes, which threatens social stability and harmony. Counterspeech is a communicative activity refuting hate speech. Scholars disagree on whether counterspeech-making behavior belongs to political participation, and their disagreements influence empirical studies on political participation. This paper uses Hannah Arendt’s conception of politics to investigate the nature of counterspeech-making behavior. It argues that this behavior is a form of political participation because it contains intrinsic political values and politics-oriented instrumental goals. The analysis broadens our knowledge of political participation and deepens our understanding of hate speech and counterspeech.

As growing evidence shows that engagement with politics is associated with worsening mental and physical health, a bumper election year and increasing polarization could affect millions.

Abstract

Journalists are often the adult public’s central source of scientific information, which means that their reporting shapes the relationship the public has with science. Yet philosophers of science largely ignore journalistic communication in their inquiries about trust in science. This paper aims to help fill this gap in research by comparing journalistic norm conflicts that arose when reporting on COVID-19 and tobacco, among other policy-relevant scientific topics. I argue that the public’s image of scientists– as depositories of indisputable, value-free facts, trustworthy only when in consensus– makes it particularly difficult for journalists to ethically communicate policy-relevant science rife with disagreement. In doing so, I show how journalists, like scientists, face the problem of inductive risk in such cases. To overcome this problem, I sketch a model of trust in science that is grounded in an alternative image of scientists– what I call the responsiveness model of trust in science. By highlighting the process of science over its product, the responsiveness model requires scientists to respond to empirical evidence and the public’s values to warrant the public’s trust. I then show why this model requires journalists to be the public’s watchdogs by verifying and communicating whether scientists are being properly responsive both epistemically and non-epistemically.

Abstract

Disorientation is a versatile, multidisciplinary concept. Whether associated with its spatial meaning or its non-spatial, more metaphorical sense, various disciplines have used disorientation to describe a broad range of philosophical, cultural, and social phenomena in the last decades. However, the focus on the concept from an emotional perspective remains scarce. To expand the current investigation on the topic, the present paper attempts a first approach to conceptualize disorientation as an emotional experience from an interactionist perspective. The paper reviews the previous literature, provides theoretical background and a working definition for the concept, and examines prototypical situations that are potentially disorienting for individuals, emphasizing the social and situated nature of the disorienting experience. The paper also comments on the relationships between disorientation and culture and points out some implications of the concept in mental health and psychological distress. Altogether, the paper argues about the value of disorientation as a powerful construct to gain insight into what, why, and how traumatic and everyday situations as well as current cultural and social challenges impact people emotionally.