Big Data &Society, Volume 11, Issue 2, April-June 2024. Self-trackers collect personal data for many reasons, including generating insight about their bodies, habits, productivity, and wellbeing. Self-tracking may expose intimate facets of daily life, raising important questions about surveillance, privacy, and data ownership. In this study, we investigated an online community of self-trackers and their weekly “show-and-tell” presentations through observations of their meetings and interviews with members. Making sense of their personal data in community with others involved practical and ..read more

Big Data &Society, Volume 11, Issue 2, April-June 2024. Content moderation algorithms influence how users understand and engage with social media platforms. However, when identifying hate speech, these automated systems often contain biases that can silence or further harm marginalized users. Recently, scholars have offered both restorative and transformative justice frameworks as alternative approaches to platform governance to mitigate harms caused to marginalized users. As a complement to these recent calls, in this essay, I take up the concept of reparation as one substantive approach ..read more

Big Data &Society, Volume 11, Issue 2, April-June 2024. This article examines the public response to mandatory location disclosure (MLD), a new surveillance technology implemented on China's Sina Weibo. Initially introduced to geo-tag posts related to the Ukraine War, the MLD eventually expanded to encompass all posts and comments on the platform. Drawing on a large-scale dataset comprising over 0.6 million posts and 24 million comments, this study uncovers political asymmetry observed during the initial implementation of MLD. Users with different political orientations were subjected to d ..read more

Big Data &Society, Volume 11, Issue 2, April-June 2024. Part of an accelerated trend to integrate algorithms in immigration decision-making, the UK's EU Settlement Scheme relies on automated data checks as an essential and mandatory step in the application for UK residence. In this article, I engage with the literature on datafication and algorithmic accuracy to showcase algorithmic inaccuracy within borders in regard to the allocation of residence statuses and rights. I argue that, while the EUSS uses big data to create a data double of the ‘desirable’ migrant, even applicants within this ..read more

Big Data &Society, Volume 11, Issue 2, April-June 2024. This article presents an ethnographic case study of a corporate-academic group constructing a benchmark dataset of daily activities for a variety of machine learning and computer vision tasks. Using a socio-technical perspective, the article conceptualizes the dataset as a knowledge object that is stabilized by both practical standards (for daily activities, datafication, annotation and benchmarks) and alignment work – that is, efforts including forging agreements to make these standards effective in practice. By attending to alignmen ..read more

Big Data &Society, Volume 11, Issue 2, April-June 2024. This study examines the impact of role-based constraints on privacy cynicism within higher education, a workplace increasingly subjected to surveillance. Using a thematic analysis of 15 in-depth interviews conducted between 2017 and 2023 with data stewards in the California State University System, the research explores the reasons behind data stewards’ privacy cynicism, despite their knowledge of privacy and their own ability to protect it. We investigate how academic data custodians navigate four role-based tensions: the conflict be ..read more

Big Data &Society, Volume 11, Issue 1, January-March 2024. Online labour markets (OLMs) are a vital source of income for globally diverse and dispersed freelancers. Despite their promise of neutrality, OLMs are known to perpetuate hiring discrimination, vested in how OLMs are designed and what kinds of interactions they enable between freelancers and hirers. In this study, we go beyond understanding mechanisms of hiring discrimination in OLMs, to identifying platform design features that can minimise hiring discrimination. To do so, we draw on a methodology guided by the design justice eth ..read more

Big Data &Society, Volume 11, Issue 1, January-March 2024. People experiencing homelessness seek support from homeless services systems that increasingly rely on prioritization algorithms to determine who is the most deserving of scarce resources. In this paper, we argue that algorithmic harms in homeless services require a reparative approach that takes the data work of care workers seriously. Building on Davis, Williams, and Yang's concept of algorithmic reparation, we present a qualitative study that examines the intertwining of data work and care labor of 15 care workers. We show how t ..read more

Big Data &Society, Volume 11, Issue 1, January-March 2024. This study investigated the factors that influence individuals’ privacy helplessness in the context of social media and mobile application use. An integrative research model was proposed, simultaneously examining both rational evaluation processes and directional motivated reasoning. The integrative research model was tested using national survey data collected from Facebook users (Study 1, n = 660) and mobile application users (Study 2, n = 385) in the US. The findings demonstrated significant associations between privacy helpless ..read more

Big Data &Society, Volume 11, Issue 1, January-March 2024. In this commentary, we examine the key ethical concerns arising from the rapid penetration and proliferation of generative artificial intelligence (AI), with ChatGPT as a prominent case study. Our analysis is structured around four pivotal themes: the debates on plagiarism and authorship in AI-generated content; the underlying power dynamics that shape biases in AI development; the dynamic, complex relationships between humans and machines; and the growing concerns over unchecked progress and the absence of accountability in the ra ..read more