Tag: Climate Change Disinformation

Abstract

Large language models (LLMs) like GPT-4 have the potential to dramatically change the landscape of influence operations. They can generate persuasive, tailored content at scale, making campaigns using falsified content, such as disinformation and fake accounts, easier to produce. Advances in self-hosted open-source models have meant that adversaries can evade content moderation and security checks built into large commercial models such as those commercialised by Anthropic, Google, and OpenAI. New multi-lingual models make it easier than ever for foreign adversaries to pose as local actors. This article examines the heightened threats posed by synthetic media, as well as the potential that these tools hold for creating effective countermeasures. It begins with assessing the challenges posed by a toxic combination of automated bots, human-controlled troll accounts, and more targeted social engineering operations. However, the second part of the article assesses the potential for these same tools to improve detection. Promising countermeasures include running internal generative models to bolster training data for internal classifiers, detecting statistical anomalies, identifying output from common prompts, and building specialised classifiers optimised for specific monitoring needs.

Abstract

The confrontations of stakeholder visions about agriculture and food production has become a focal point in the public sphere, coinciding with a diversification of agrifood models. This study analyzes the debates stemming from the coexistence of these models, particularly during the initial term of neoliberal-centrist Emmanuel Macron’s presidency in France. Employing collective monitoring from 2017 to 2021, a corpus of 958 online news and blog articles was compiled. Using a computational analysis, we reveal the framings and controversies emerging from this media discourse. The macro-structuring of discourse on model coexistence revolves around scientific, economic and political framings. Coexistence is a complex of debates based on specific frames associated with specific arenas and actor configurations: growth of organic agriculture, transformations of agrifood systems, sciences of production and impacts, livestock and meat diet controversies, agroecological innovations, CAP reform criticism, discourse of peasant agriculture and State-Profession co-gestion. Employing global sentiment analysis and focusing on salient controversies, namely EGAlim law, pesticide regulations, and agribashing, we show the shift from conciliation to a hardening of debates. Finally, we discuss the causes and consequences of this trend. The political will to support the transition of agriculture remains influenced by the co-gestion system, an inherited configuration of decision-makers instrumental in the agricultural modernization. As a consequence, significant agricultural challenges, particularly highlighted in the scientific macro-frame, persist unresolved. This lock-in of the agrifood system is based on defensive strategies that challenge the democratic debate about food and agricultural practices.

Abstract

Türkiye has a long history of devastating earthquakes, and on February 6, 2023, the region experienced two major earthquakes with magnitudes of 7.7 and 7.6, striking Pazarcık and Elbistan, Kahramanmaraş, respectively, on the East Anatolian Fault Zone. These earthquakes resulted in significant loss of life and property, impacting multiple cities across 11 cities, and leaving a lasting impact on the country. The 2023 Kahramanmaraş Earthquakes rank among the deadliest and most damaging earthquakes in Türkiye, alongside the historical significance of the 1939 Erzincan Earthquake and the 1999 Marmara Earthquake. Despite reforms following the 1999 Marmara Earthquake in disaster policy and preparedness, the scale of damage from the February 6 earthquakes has been shocking, necessitating further insights and lessons for future earthquake management. This paper presents the outcomes of immediate response efforts organized after the 2023 Kahramanmaraş earthquakes to elucidate emergency response activities and their impacts on communities, considering the substantial size and severity of the damages. The study focuses on evaluating the emergency response provided within the first 24 h, 3 days, and 2 weeks after the earthquakes, aiming to promptly identify the nature and effectiveness of these responses, as well as the conditions that hindered their efficacy. By shedding light on the specific experiences and challenges faced during these crucial timeframes, the research aims to offer valuable insights and lessons learned. These findings contribute to improved preparedness strategies and more efficient emergency response measures needed in responding to future disaster scenarios. Ultimately, this study provides a useful resource for all stakeholders involved in emergency response and disaster management, offering valuable guidance to enhance resilience and preparedness in the face of seismic hazards.

Abstract

Under the threat of the novel coronavirus, people are compelled to contemplate some ultimate existential questions, such as life and death. This study collected texts related to the death psychology from Sina Weibo, and after data cleaning, a total of 3868 Weibo texts were included. Study 1 employed grounded theory from qualitative research to explore the core categories and evolutionary mechanisms of people's psychology when facing death threats in the context of the pandemic. Study 2 utilized big data mining techniques such as topic mining and semantic network analysis to validate the effectiveness of the death psychology theory developed in qualitative research. The findings demonstrate that within the “Emotion–Cognition–Behavior-Value” framework, the implications of death threats manifest in four aspects: death anxiety, death cognition, coping efficacy, and sense of meaning. As time progresses, the study of death psychology can be segmented into four distinct phases: the tranquil phase prior to lifting pandemic restrictions, the threat phase at lifting pandemic restrictions onset, the coping phase mid-lifting pandemic restrictions, and the reformative phase post-lifting pandemic restrictions. The calculated outcomes of topic mining and semantic network analysis corroborate the coding results and theories derived from the grounded theory. This reaffirms that data mining technology can be a potent tool for validating grounded theory.

Abstract

Effective digital literacy interventions can positively influence social media users’ ability to identify fake news content. This research aimed to (a) introduce a new experiential training digital literacy intervention strategy, (b) evaluate the effect of different digital literacy interventions (i.e., priming critical thinking and an experiential training exercise) on the perceived accuracy of fake news and individuals’ subsequent online behavioral intentions, and (c) explore the underlying mechanisms that link various digital literacy interventions with the perceived accuracy of fake news and online behavioral intentions. The authors conducted a study, leveraging online experimental data from 609 participants. Participants were randomly assigned to different digital literacy interventions. Next, participants were shown a Tweeter tweet containing fake news story about the housing crisis and asked to evaluate the tweet in terms of its accuracy and self-report their intentions to engage in online activities related to it. They also reported their perceptions of skepticism and content diagnosticity. Both interventions were more effective than a control condition in improving participants’ ability to identify fake news messages. The findings suggest that the digital literacy interventions are associated with intentions to engage in online activities through a serial mediation model with three mediators, namely, skepticism, perceived accuracy and content diagnosticity. The results point to a need for broader application of experiential interventions on social media platforms to promote news consumers’ ability to identify fake news content.

Abstract

Effective digital literacy interventions can positively influence social media users’ ability to identify fake news content. This research aimed to (a) introduce a new experiential training digital literacy intervention strategy, (b) evaluate the effect of different digital literacy interventions (i.e., priming critical thinking and an experiential training exercise) on the perceived accuracy of fake news and individuals’ subsequent online behavioral intentions, and (c) explore the underlying mechanisms that link various digital literacy interventions with the perceived accuracy of fake news and online behavioral intentions. The authors conducted a study, leveraging online experimental data from 609 participants. Participants were randomly assigned to different digital literacy interventions. Next, participants were shown a Tweeter tweet containing fake news story about the housing crisis and asked to evaluate the tweet in terms of its accuracy and self-report their intentions to engage in online activities related to it. They also reported their perceptions of skepticism and content diagnosticity. Both interventions were more effective than a control condition in improving participants’ ability to identify fake news messages. The findings suggest that the digital literacy interventions are associated with intentions to engage in online activities through a serial mediation model with three mediators, namely, skepticism, perceived accuracy and content diagnosticity. The results point to a need for broader application of experiential interventions on social media platforms to promote news consumers’ ability to identify fake news content.

Abstract

Misinformation, lack of trust, and uncertainty during the COVID-19 pandemic have fostered the emergence of new conspiracy theories. In August 2021, we examined the association of individual personality traits and socio-environmental factors with high belief in pandemic-related conspiracies through an online survey among 3,067 quota-sampled German-speaking adults residing in the D-A-CH region (Germany, Austria, Switzerland). In multivariable-adjusted regression models, pandemic-related conspiracy belief was, first, negatively associated with tertile (T) of complexity thinking, optimism, and higher level of education (complexity thinking, OR_T3vs.T1: 0.43, 95% CI 0.32–0.57, P_trend < 0.01; optimism, OR_T3vs.T1: 0.41, 95% CI: 0.30–0.56, P_trend < 0.01; higher education, OR_{T3vs. T1}: 0.67, 0.50-0.89; P_trend <0.01) and second, positively associated with regular participation in religious meetings, not having recently voted, unwillingness of oneself or one’s close contacts to vaccinate, past COVID-19 infection and disapproval of COVID-19 mitigation measures. Our findings highlight the importance to foster complexity understanding through targeted interventions, such as in education settings, to help curb the spread of conspiracy theories. We conclude that, in order to effectively address the challenges posed by pandemic-related conspiracy theories, policymakers must acknowledge the impact of conspiracy beliefs on public health decisions while promoting transparent communication and interdisciplinary (between scientific disciplines) and transdisciplinary (between science and society) research, as well as science literacy and science diplomacy collaboration.

Abstract

Misinformation, lack of trust, and uncertainty during the COVID-19 pandemic have fostered the emergence of new conspiracy theories. In August 2021, we examined the association of individual personality traits and socio-environmental factors with high belief in pandemic-related conspiracies through an online survey among 3,067 quota-sampled German-speaking adults residing in the D-A-CH region (Germany, Austria, Switzerland). In multivariable-adjusted regression models, pandemic-related conspiracy belief was, first, negatively associated with tertile (T) of complexity thinking, optimism, and higher level of education (complexity thinking, OR_T3vs.T1: 0.43, 95% CI 0.32–0.57, P_trend < 0.01; optimism, OR_T3vs.T1: 0.41, 95% CI: 0.30–0.56, P_trend < 0.01; higher education, OR_{T3vs. T1}: 0.67, 0.50-0.89; P_trend <0.01) and second, positively associated with regular participation in religious meetings, not having recently voted, unwillingness of oneself or one’s close contacts to vaccinate, past COVID-19 infection and disapproval of COVID-19 mitigation measures. Our findings highlight the importance to foster complexity understanding through targeted interventions, such as in education settings, to help curb the spread of conspiracy theories. We conclude that, in order to effectively address the challenges posed by pandemic-related conspiracy theories, policymakers must acknowledge the impact of conspiracy beliefs on public health decisions while promoting transparent communication and interdisciplinary (between scientific disciplines) and transdisciplinary (between science and society) research, as well as science literacy and science diplomacy collaboration.

Abstract

Catering to a primarily male user population, Reddit is often said to be a breeding ground for toxic language use, which has led to the development of multiple computational classification models for the automated identification of toxicity in online conversations. Since negation can play a key role in cyberbullying, functioning as a popular stance marker in the dialogical exchange of dominating views in the digital sphere, it should not be ignored. Likewise, its use as a rhetorical strategy deserves more linguistic attention. Described as Engagement resources of disclaim in Appraisal theory, negated constructions may be employed by Reddit users to disalign themselves from divergent perspectives through emotion-driven ad hominem attacks, not only resulting in a potentially detrimental impact on the users’ mental health, but also perpetuating toxic power relationships. Therefore, this paper examines the use of negation, in combination with various other interpersonal resources, within the Redditors’ dialogical interactions, to explore its possible motivations and role in shaping the online discourse. A computer-assisted appraisal analysis was conducted on 2637 most upvoted comments and replies (49,866 words), extracted from the subreddit of r/AustralianPolitics between 11–14 April and 7–10 May 2022, during the period leading up to the so-called federal climate change election in Australia. The study shows evidence of a seemingly dominant negation pattern characterised by negative judgement and its findings tentatively suggest that some of the male Australian users may use negation as a discursive strategy driven by ideology and emotion. This raises the possibility that the language use encountered on r/AustralianPolitics may be influenced by covert toxic geek masculinity.