Understood as the practices that seek to centre and empower individuals and communities in the collection, usage and sharing of data, the concept of participatory data stewardship (PDS) is often praised for its potential to challenge datafication and facilitate public involvement in decision-making processes mediated by and about data. However, little is known about the role of data literacies – the skills, knowledge and practices involved in accessing and using data both practically and, more critically, with a view to civic action and social change – within PDS. Based on semi-structured interviews with community researchers (CRs) taking part in a PDS project conducted in Widnes, a town in the UK, this article examines the importance of developing CRs’ data literacies in the context of their involvement in the project. Key findings suggest that, whilst CRs recognised significant gaps in their data literacies, with data often being referred to as an abstract and obscure concept, they had both strong motivations to better understand data and expectations for how this may be used to improve their community. Bridging media literacy research on critical data literacies with PDS research, this paper argues that, if we are to expect PDS to potentially empower communities in a datafied society, then members of these communities need to be supported to develop their data literacies. Implications for research, practice and policy are discussed.

This paper critically examines science communication discourse produced through AI-generated podcasts, created via Google NotebookLM. We propose a rhetorical-argumentative framework to verify whether podcasts mediating scientific reports propagate quality discourse or mis−/dis-information. We apply this framework to the qualitative analysis of a corpus of podcasts stemming from scientific reports about communication and media research. The study reveals that podcasts produced via the ‘Audio Overview’ feature of Google NotebookLM, though engaging, trivialize content, propagate biases, and draw unwarranted inferences that misrepresent authors' intentions. The integration of dialectical and rhetorical components within our discourse analysis surfaced the presence of fallacies and misleading ways of packaging and presenting information. This misrepresentation risks undermining research integrity, as authors are not guaranteed the opportunity to verify the accuracy of their work before dissemination, and it spreads misinformation, instead of ensuring quality science communication to inform policymaking.

Despite efforts to promote media literacy provision (i.e., the support provided to develop people's media literacy within and outside formal education) in the UK, this provision remains fragmented, under-supported, and under-evaluated. Employing a case study methodology, this article explores the state of media literacy policy and provision within five areas of the UK: Birmingham and the West Midlands, Greater Manchester, Liverpool City Region, Scotland, and Wales. Based on semi-structured interviews with policymakers and representatives of civil society organisations, key findings suggest that government bodies within all five areas have established digital inclusion networks, with media literacy provision piggybacking on these networks. While best practice is often based on forms of collaboration (e.g., to access target populations, co-design/co-deliver initiatives), significant barriers remain, including funding and the lack of an overarching framework for coordinating media literacy provision across the UK. The implications of these findings for research, policy, and practice are discussed.

IntroductionTraditional data and measures about health and well-being provide vital insights but do not provide context on the ways in which a community may want to see development in their local area. This article is based on a Participatory Action Research (PAR) project on well-being and data conducted with members of a community in Widnes, a town in the UK. We explore the usefulness of adapting a PAR methodology to develop a Participatory Data Stewardship (PDS) program at the community level.MethodsThrough repeated, semi-structured interviews, we tracked 15 Community Researchers' (CRs') experiences and perspectives of taking part in a PDS/PAR project. CRs were purposely recruited to primarily maximize diversity in gender, age, and socio-economic status, and interviewed before training, after training, and after fieldwork. We used thematic analysis to explore benefits and challenges, along with their expectations and experiences, at each stage of the project.ResultsFour main themes emerged from interviews with CRs on their expectations and experiences: (1) the role of CRs' motivation in taking part on their perceptions of project impact, (2) the role and development of confidence in CRs' perceptions of their own success, (3) the importance of community building through an appreciation of diversity, and (4) the value in developing CR agency by putting participatory process at each stage of the project.DiscussionThe findings illustrate that taking a PAR approach to the design of a PDS project around well-being and data shows potential for problematizing datafication through engaging local communities, developing their research skills, confidence and agency, and designing a data system that can empower community voice. This article addresses a gap in the literature on the feasibility of taking a PAR approach to the implementation of PDS. Future research should build on this study to explore the conditions for successful PAR in the context of other PDS projects.

In the fast-paced, densely populated information landscape shaped by digitization, distinguishing information from misinformation is critical. Fact-checkers are effective in fighting fake news but face challenges such as cognitive overload and time pressure, which increase susceptibility to cognitive biases. Establishing standards to mitigate these biases can improve the quality of fact-checks, bolster audience trust, and protect against reputation attacks from disinformation actors. While previous research has focused on audience biases, we propose a novel approach grounded on relevance theory and the argumentum model of topics to identify (i) the biases intervening in the fact-checking process, (ii) their triggers, and (iii) at what level of reasoning they act. We showcase the predictive power of our approach through a multimethod case study involving a semi-automatic literature review, a fact-checking simulation with 12 news practitioners, and an online survey involving 40 journalists and fact-checkers. The study highlights the distinction between biases triggered by relevance by effort and effect, offering a taxonomy of cognitive biases and a method to map them within decision-making processes. These insights can inform trainings to enhance fact-checkers’ critical thinking skills, improving the quality and trustworthiness of fact-checking practices.

AbstractIn this chapter we present our own work on developing the idea of Data Literacy and reflect on the potential to develop democratic education for data citizenship. In our work we link ideas from Dewey (New Republic 61:294–296, 1930) and Freire (Pedagogy of the oppressed (revised). Continuum, 1970/1996), with ideas from Nussbaum (Int Stud Rev 4(2), 123–135, 2002) and Sen (The idea of justice. Harvard University Press, 2009), to consider how we move towards a more just datafied society (see Carmi E, Yates S, Int J Commun 17:3619–3637, 2023). We argue that Data Literacy and Data Citizenship interventions need to build on a deep understanding of their audience and their journey towards greater data citizenship and awareness of issues in our datafied society. The chapter sets out seven principles for the development of Data Literacy and data citizenship support interventions and explores approaches to their development.

We argue here that data literacies and capabilities are an integral part of data justice. Based on focus group data collected as part of a 3-year empirical project research project, we find that citizens remain unaware of key aspects of the digital ecosystem, which exacerbate the power imbalance between big technology (data processors) companies and citizens ( data subjects). Citizens feel concerned about the way it is operating, they do not feel confident enough to be able to address that. We find that "networks of literacy" among friends, colleagues, and trusted organizations are crucial for citizens' capabilities. These networks influence citizens' ability to convert their available means into capabilities to support civic engagement and their communities.

To counter the fake news phenomenon, the scholarly community has attempted to debunk and prebunk disinformation. However, misinformation still constitutes a major challenge due to the variety of misleading techniques and their continuous updates which call for the exercise of critical thinking to build resilience. In this study we present two open access chatbots, the Fake News Immunity Chatbot and the Vaccinating News Chatbot, which combine Fallacy Theory and Human–Computer Interaction to inoculate citizens and communication gatekeepers against misinformation. These chatbots differ from existing tools both in function and form. First, they target misinformation and enhance the identification of fallacious arguments; and second, they are multiagent and leverage discourse theories of persuasion in their conversational design. After having described both their backend and their frontend design, we report on the evaluation of the user interface and impact on users’ critical thinking skills through a questionnaire, a crowdsourced survey, and a pilot qualitative experiment. The results shed light on the best practices to design user-friendly active inoculation tools and reveal that the two chatbots are perceived as increasing critical thinking skills in the current misinformation ecosystem.

AbstractThe Networked Society has brought about opportunities, such as citizens’ journalism, as well as challenges, such as the proliferation of media distortions. To keep up which such a sheer amount of (mis)information, citizens need to develop critical media literacy. We believe that, even though not enough to guarantee a gatekeeping process, human-computer interaction can help users develop epistemic vigilance. To this sake, we present the Fake News Immunity chatbot, designed to teach users how to recognize misinformation leveraging Fallacy Theory. Fallacies, arguments which seem valid but are not, constitute privileged viewpoints for the identification of misinformation. We then evaluate the results of the chatbot as an educational tool through a gamification experience with two cohorts of students and discuss achieved learning outcomes as well as recommendations for future improvement.

We argue here that data literacies and capabilities are an integral part of data justice. Based on focus group data collected as part of a 3-year empirical project research project, we find that citizens remain unaware of key aspects of the digital ecosystem, which exacerbate the power imbalance between big technology (data processors) companies and citizens (data subjects). Citizens feel concerned about the way it is operating, they do not feel confident enough to be able to address that. We find that “networks of literacy” among friends, colleagues, and trusted organizations are crucial for citizens’ capabilities. These networks influence citizens’ ability to convert their available means into capabilities to support civic engagement and their communities.

While most research using online (video conferencing) focus groups take for granted people’s digital access and skills, in this chapter we consider work we undertook with people who have low digital literacy levels. We conducted the work during the COVID-19 pandemic and under social distancing regulations, shifting from a face-to-face workshop design to online focus groups. Our findings highlight the ways online focus groups can be successfully delivered when considering those with low digital literacy. Factors including smaller group sizes, joining remote sessions using individual devices, considering and categorising user types, pursuing follow-up questions, and providing contextual examples. These insights are useful for designing, developing, and conducting both ethical and considerate remote focus groups. We found that the literacy levels of your participants shape the way the session will run and that moving online adds another layer of complexity requiring constant adjustments and reflections. This work was part of our Nuffield Foundation funded project “Me and My Big Data: Developing Citizens Data Literacies” that was conducted between 2018-2021.

Misinformation constitutes one of the main challenges to counter the infodemic: misleading news, even if not blatantly false, can cause harm especially in crisis scenarios such as the pandemic. Due to the fast proliferation of information across digital media, human fact-checkers struggle to keep up with fake news, while automatic fact-checkers are not able to identify the grey area of misinformation. We, thus, propose to reverse engineer the manipulation of information offering citizens the means to become their own fact-checkers through digital literacy and critical thinking. Through a corpus analysis of fact-checked news about COVID-19, we identify 10 fallacies-arguments which seem valid but are not-that systematically trigger misinformation and offer a systematic procedure to identify them. Next to fallacies, we examine the types of sources associated to (mis-/dis-)information in our dataset as well as the type of claims making up the headlines. The statistical patterns surfaced from these three levels of analysis reveal a misinformation ecosystem where no source type is exempt from flawed arguments with frequent evading the burden of proof and cherry picking behaviors, even when descriptive claims are at stake. In such a scenario, exercising the audience's critical skills through fallacy and semantic analysis is necessary to guarantee fake news immunity.

In this paper we present the findings from the third phase of our (redacted) project on citizens data literacies. The data literacies framework we developed - Data Citizenship - stemmed from an analysis of recent literature on data and digital literacy combined with ideas from democratic education. In particular, we focus on the power imbalance between citizens and ‘big-tech’ and government entities who access, process and use data about citizens and their networks. We argue that due to its collective, socially contextualised, and people-centred qualities, democratic education provides a useful foundation for future data literacy education and research interventions. Following an extensive literature review (first phase), and then a UK nationally representative survey (phase 2), we have conducted focus groups during Autumn 2020 and Winter 2021 with citizens.

This article presents preliminary results of the first two research stages of the Me and My Big Data research project: (1) a systematic literature review, and (2) a nationally representative survey of UK citizens’ data literacy. The analysis reveals some contradictions between how citizens think about the truthfulness of online information (e.g., online news) and what they do to verify its accuracy (e.g., fact-checking), and suggests that these contradictions might be related to citizens' limited data literacy levels.