Search Results (6)

Disinformation refers to false or misleading information created with the deliberate intention to deceive and cause individual or societal harm. It is typically distinguished from misinformation, which involves falsehoods shared without deceptive intent, and from malinformation, which uses accurate information in misleading or harmful ways. Terms often used interchangeably in public debate—such as fake news, propaganda, and conspiracy theories—describe related but distinct phenomena with differing aims and methods. The term derives from the Soviet concept of dezinformatsiya, originally associated with covert influence operations and strategic deception. Over time, however, its meaning has expanded to encompass a wide range of manipulative practices enacted by both state and non-state actors. Disinformation can take textual, visual, and multimodal forms, including fabricated images and AI-generated content such as deepfakes. Motivations vary and may include political influence, economic gain, ideological mobilisation, or efforts to stigmatise specific groups. Although these practices have long historical precedents, digital and platformised communication environments have amplified their scale, speed, and persuasive potential. This entry provides a narrative overview and conceptual synthesis structured around four dimensions: the history of disinformation, the supply and diffusion mechanisms, the psychological, social, and narrative drivers, and the interventions designed to mitigate its impact. Full article

Since the WHO declared COVID-19 a pandemic, prominent social actors and institutions have warned about the threat of misinformation, calling for policy action to address it. However, neither the premises underlying expert claims nor the standards to separate truth from falsehood have been appraised. We conducted a scoping review of the medical and social scientific literature, informed by a critical policy analysis approach, examining what this literature means by misinformation. We searched academic databases and refereed publications, selecting a total of 68 articles for review. Two researchers independently charted the data. Our most salient finding was that verifiability relied largely on the claims of epistemic authorities, albeit only those vetted by the establishment, to the exclusion of independent evidentiary standards or heterodox perspectives. Further, “epistemic authority” did not depend necessarily on subject matter expertise, but largely on a new type of “expertise”: in misinformation itself. Finally, policy solutions to the alleged threat that misinformation poses to democracy and human rights called for suppressing unverified information and debate unmanaged by establishment approved experts, in the name of protecting democracy and rights, contrary to democratic practice and respect for human rights. Notably, we identified no pockets of resistance to these dominant meanings and uses. We assessed the implications of our findings for democratic public policy, and for fundamental rights and freedoms. Full article

Disinformation is a phenomenon of concern to all political systems, as it poses a threat to freedom and democracy through the manipulation of public opinion aimed at eroding institutions. This paper presents a bibliometric and systematized study which allows the establishment of a comprehensive view of the research and current state of academic investigations on disinformation. To this end, a content analysis of the scientific articles indexed in Scopus up to 31 December 2023 has been carried out based on three categories of analysis: journals, authors and investigations. Similarly, a systematic study of the 50 most cited articles in this sample was performed in order to gain a deeper understanding of the nature, motivations and methodological approaches of these investigations. The results indicate that disinformation is a research topic which has gained great interest in the academic community since 2018, with special mention to the impact of COVID-19 and the vaccines against this disease. Thus, it can be concluded that disinformation is an object of study which attracts significant attention and which must be approached from transdisciplinarity to respond to a phenomenon of great complexity. Full article

The ubiquity of social and online media networks, the credulousness of online communities, coupled with limited accountability pose a risk of mis-, dis-, mal-, information (mis-dis-mal-information)—the intentional or unintentional spread of false, misleading and right information related to agri-food topics. However, agri-food mis-dis-malinformation in social media and online digital agricultural communities of practice (CoPs) remains underexplored. There is also a limited theoretical and conceptual foundation for understanding mis-dis-malinformation topics in the agri-food sectors. The study aims to review mis-dis-malinformation literature and offer a framework to help understand agri-food mis-dis-malinformation in social media and online CoPs. This paper performs a systematic review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The review shows that many disciplines, particularly communication, social media studies, computer science, health studies, political science and journalism, are increasingly engaging with mis-dis-malinformation research. This systematic research generates a framework based on six thematic categories for holistically understanding and assessing agri-food mis-dis-malinformation in social and online media communities. The framework includes mis-dis-malinformation characterization, source identification, diffusion mechanisms, stakeholder impacts, detection tactics, and mis-dis-malinformation curtailment and countermeasures. The paper contributes to advancing the emerging literature on ‘controversial topics’, ‘misinformation’, and ‘information integrity’ of the virtual agri-food advisory services. This is the first attempt to systematically analyze and incorporate experience from diverse fields of mis-dis-malinformation research that will inform future scholarly works in facilitating conversations and advisory efforts in the agri-food sector. Full article

Interest in research connected to information disorders has grown considerably in recent years. The phrase “information disorders” refers to three different notions: dis-, mis-, and malinformation. It is difficult to pin down this new and dynamic phenomenon of informational disruption and to assess its impact on society. Therefore, we conducted a bibliometric analysis on the complexity of information disorders using the Web of Science Core Collection database from 1975 to June 2021. We analyzed 8964 papers with the goal to have an overall picture of the topic, clarify the knowledge framework of research in this field, examine the development dynamics, identify future research directions and increase the understanding of the research on information disorders. The following are our main findings: the number of publications, authors, and journals has increased; research on information disorders has earned considerable attention in multiple academic fields; there are more and more works written in collaboration by scholars from different parts and cultures of the world. This paper makes important contributions to the literature, not only by providing researchers and practitioners with a coherent and perceptible intellectual basis to find answers, but also by bringing valuable insights for further investigation and future research directions. Full article

Even with advances in climate modeling, meteorological impact assessment remains elusive, and decision-makers are forced to operate with potentially malinformed predictions. In this article, we investigate the dependence of the Weather Research and Forecasting (WRF) model simulated precipitation and temperature at 12- and 4-km horizontal resolutions and compare it with 32-km NARR data and 1/16th-degree gridded observations for the Midwest U.S. and Great Lakes region from 1991 to 2000. We used daily climatology, inter-annual variability, percentile, and dry days as metrics for inter-comparison for precipitation. We also calculated the summer and winter daily seasonal minimum, maximum, and average temperature to delineate the temperature trends. Results showed that NARR data is a useful precipitation product for mean warm season and summer climatological studies, but performs extremely poorly for winter and cold seasons for this region. WRF model simulations at 12- and 4-km horizontal resolutions were able to capture the lake-effect precipitation successfully when driven by observed lake surface temperatures. Simulations at 4-km showed negative bias in capturing precipitation without convective parameterization but captured the number of dry days and 99^th percentile precipitation extremes well. Overall, our study cautions against hastily pushing for increasingly higher resolution in climate studies, and highlights the need for the careful selection of large-scale boundary forcing data. Full article