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Trust in data practices and data-driven systems is widely seen as both important and elusive. A data trust deficit has been identified, to which proposed solutions are often localised or individualised, focusing either on what institutions can do to increase user trust in their data practices or on data management models that empower the individual user. Scholarship on trust often focuses on typologies of trust. This paper shifts the emphasis to those doing the trusting, by presenting findings from empirical research which explored user perspectives on the data practices of the BBC. These findings challenge the assumption that localised or individualised solutions can be effective. They also suggest that conceptualisations of trust in data practices need to account for the complex range of factors which come into play in relation to trust in data and so move beyond the production of typologies. In this paper, we propose the concept of 'complex ecologies of trust' as a way of addressing all of these issues. [ABSTRACT FROM AUTHOR]

This paper argues that visualisation conventions work to make the data represented within visualisations seem objective, that is, transparent and factual. Interrogating the work that visualisation conventions do helps us to make sense of the apparent contradiction between criticisms of visualisations as doing persuasive work and visualisation designers’ belief that through visualisation, it is possible to ‘do good with data’ [Periscopic. 2014.Home page. Retrieved fromhttp://www.periscopic.com/]. We focus on four conventions which imbue visualisations with a sense of objectivity, transparency and facticity. These include: (a) two-dimensional viewpoints; (b) clean layouts; (c) geometric shapes and lines; (d) the inclusion of data sources. We argue that thinking about visualisations from a social semiotic standpoint, as we do in this paper by bringing together what visualisation designers say about their intentions with a semiotic analysis of the visualisations they produce, advances understanding of the ways that data visualisations come into being, how they are imbued with particular qualities and how power operates in and through them. Thus, this paper contributes nuanced understanding of data visualisations and their production, by uncovering the ways in which power is at work within them. In turn, it advances debate about data in society and the emerging field of data studies. [ABSTRACT FROM AUTHOR]

This paper draws on empirical research with NEET populations (16–24-year-olds not in education, employment or training) in the U.K. in order to engage with issues around identification, data and metrics produced through datalogical systems. Our aim is to bridge contemporary discourses around data, digital bureaucracy and datalogical systems with empirical material drawn from a long-term ethnographic project with NEET groups in Leeds, U.K. in order to highlight the way datalogical systems ideologically and politically shape people’s lives. We argue that NEET is a long-standing data category that does work and has resonance within wider datalogical systems. Secondly, that these systems are decision-making and far from benign. They have real impact on people’s lives – not just in a straightforwardly, but in obscure, complex and uneven ways which makes the potential for disruption or intervention increasingly problematic. Finally, these datalogical systems also implicate and are generated by us, even as we seek to critique them. [ABSTRACT FROM PUBLISHER]

This paper explores the relationships of subjects in the context of data and data technologies, and advances an original theoretical framework called Informatic Personhood to better conceptual subjects and their relationships. Because of the enormous structural change that data has contributed to, subjects are sometimes distant and backgrounded in studies of data, despite data having significant impacts on their lives. Data-mediated relationships mean an increased scale to a relationship, with individuals able to connect to much broader contexts of data, but also have these structures reach down to their subjective context through data. Informatic Personhood seeks to capture the dynamics of data present in everyday life, addressing this distance and better conceptualising the scale of data-mediated relationships. This framework has two parts. The first – The Informatic Context – explores salient structural developments around data and conceptualises this as being defined by the presence of 'data interfaces' (that connect individuals to digital contexts), 'data circulation' (trends in the movement and storage of data), and 'data abstraction' (data manipulation practices). The second part concerns the Informatic Person, and the embodied, affective, and sensemaking relationships of individuals occurring across and through the Informatic Context. This framework better addresses the scale of data-mediated relationships, and places subjects firmly in the foreground of how data is understood. [ABSTRACT FROM AUTHOR]

This paper examines how participatory inequalities are (re)produced in eDeliberation, a practice that purposely fosters open, fair, and rational discussions among citizens over the Internet. Relying on the theoretical traditions of Bourdieu's capital and actor-network theory, this paper proposes that technical capital, along with social, economic, cultural, and symbolic capital, function in eDeliberation as inequality makers. Two cases of eDeliberation practices conducted in the United States serve as the sources of data. Both statistical analyses of close-ended questions and a qualitative content analysis of open-ended questions from surveys were used to generate the empirical findings. Technical capital is found to reproduce existing inequalities through the unequal accumulation rates and the unbalanced convertibility associated with different actors. Both theoretical and practical implications of the findings are suggested. [ABSTRACT FROM AUTHOR]

Quantified Self (QS) is a group that coordinates a global set of in-person meetings for sharing personal experiences and experiments with self-tracking behaviours, moods, and activities. Through participation in US-based QS events and watching online QS presentations from around the globe, we identify a function of ambiguous valuation for supporting sharing communities. Drawing on Stark's (2011) theory of heterarchy, we argue that the social and technical platforms supporting sharing within the QS community allow for multiple, sometimes conflicting, sets of community and commercial values. Community cohesion benefits from ambiguity over which values set is most important to QS members. Ambiguity is promoted by sharing practices through at least two means, the narrative structure of members' presentations, and what counts as tracking. By encouraging members to adhere to a three-question outline, the community ensures that multiple values are always present. Thus, it becomes a question of which values this sharing community emphasizes, not which value sets members present, at any given time. By leaving the tools and methods of tracking open − from sophisticated wearables and data analysis to pen-and-paper and storytelling − the community creates space for and embraces self-trackers with a broad spectrum of technological proficiency and interest. QS as a group capitalizes on circulation of knowledge valued somewhat ambiguously to sustain and grow the community, both encouraging and supporting the commercialization of self-tracking technologies while keeping technology developer interests from overwhelming community-building interests. This, we argue, has implications for researchers hoping to understand online communities and the ‘sharing economy' more generally. [ABSTRACT FROM PUBLISHER]

Much as ecology emerged from biology as scientists began studying the complex interactions between organisms in their environments, a shift is happening in communication and media studies regarding analysis of social media. The complex relationships between user-generated social media and professionally created news media are best understood as a complex media ecosystem with its own emergent behaviors that only become visible when studied from a perspective broader than considering a single medium in isolation. Some of the key debates regarding social media's effects in spreading mis- and disinformation can be studied in richer ways by applying quantitative methods that integrate information across multiple types of media using a media ecosystem model. Understanding these characteristics of media ecosystems could help political parties, activists and others who depend on media to advance their messages. [ABSTRACT FROM AUTHOR]

This special issue of Information, Communication and Society reflects on the generative work presented at the 2019 annual conference of the Association of Internet Researchers (#AoIR2019). The conference attracted approximately 380 people from 35 countries to work through the theme, Trust in the System. Delegates analysed developments on the internet, in social media and through data management, including those grounded in Indigenous perspectives and varied communities, resiliencies and collective voices. Plenary provocations prompted discussions about our various relationships with "trust", "system" and "the", while research sites included webtoons and webnovels, fans and games, chemsex and porn, the rise of digital assistants and evolving digital practices in politics, health, education, environment and the media. Creative industries, automation and platformization figured broadly. Ethics, methods and theory ranged from science and technology studies (STS) to queer and indigenous theory to algorithmic approaches, digital ethnography, creative methods, and emergent work in bot detection across social media. The resulting articles curated for this collection are offered by emerging to established scholars, from around the world. [ABSTRACT FROM AUTHOR]

It could be argued that the power of data is located in what they are used to reveal. Yet we have little understanding of the role played by the emerging industry of data analytics in the interpretation and use of big data. These data analytics companies act as intermediaries in the digital data revolution. Understanding the social influence of big data requires us to understand the role played by data analytics within organisations of different types. This particular article focuses very specifically upon the way in which data and data analytics are envisioned within the marketing rhetoric of the data analytics industry. It is argued that to understand the spread of data analytics and the adoption of certain analytic strategies, we first need to look at the projection of promises upon that data. The way that data and analytics are imagined shapes their incorporation and appropriation into practices and organisational structures – what I call here thedata frontiers. This article draws upon a sample of 34 data analytics companies in order to explore the way in which data analytics are envisioned within that increasingly powerful industry. [ABSTRACT FROM AUTHOR]