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The EU Settlement Scheme: Footprints in quicksand Big Data & Society (IF 8.731) Pub Date : 2024-04-15 Cristina Juverdeanu
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
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Role-based privacy cynicism and local privacy activism: How data stewards navigate privacy in higher education Big Data & Society (IF 8.731) Pub Date : 2024-04-03 Mihaela Popescu, Lemi Baruh, Samuel Sudhakar
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
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Agreements ‘in the wild’: Standards and alignment in machine learning benchmark dataset construction Big Data & Society (IF 8.731) Pub Date : 2024-04-03 Isak Engdahl
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)
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Imaginaries of democratization and the value of open environmental data: Analysis of Microsoft's planetary computer Big Data & Society (IF 8.731) Pub Date : 2024-04-03 Przemyslaw Matt Lukacz
The proliferation of environmentally oriented programs within the tech industry, and the industry's coinciding efforts toward data and technology democratization, generate concerns about the status of environmental data within digital economy. While the accumulation of digital personal data has been a cornerstone of domination of the data analytics industry, many believe environmental data to be a
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Designing for justice in freelancing: Testing platform interventions to minimise discrimination in online labour markets Big Data & Society (IF 8.731) Pub Date : 2024-03-30 Siân Brooke, Aliya Hamid Rao
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
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AI and discriminative decisions in recruitment: Challenging the core assumptions Big Data & Society (IF 8.731) Pub Date : 2024-03-30 Päivi Seppälä, Magdalena Małecka
In this article, we engage critically with the idea of promoting artificial intelligence (AI) technologies in recruitment as tools to eliminate discrimination in decision-making. We show that the arguments for using AI technologies to eliminate discrimination in personnel selection depend on presuming specific meanings of the concepts of rationality, bias, fairness, objectivity and AI, which the AI
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Responding to unusual government request for user data: How tech companies make sense of human rights Big Data & Society (IF 8.731) Pub Date : 2024-03-26 Isabel Ebert
Data sharing practices between governments and the private sector are characterized by a lack of transparency which has potential implications for human rights. Minimal scholarship exists investigating how companies address human rights risks stemming from government requests for user data. Understanding corporate response processes to government requests is central to advancing human rights research
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Navigating the ethical landscape behind ChatGPT Big Data & Society (IF 8.731) Pub Date : 2024-03-21 Lizhi Peng, Bo Zhao
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
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After automation: Homelessness prioritization algorithms and the future of care labor Big Data & Society (IF 8.731) Pub Date : 2024-03-21 Pelle Tracey, Patricia Garcia
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
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The interplay of rational evaluation and motivated reasoning in privacy helplessness: An integrative approach Big Data & Society (IF 8.731) Pub Date : 2024-03-21 Hichang Cho
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)
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A typology of artificial intelligence data work Big Data & Society (IF 8.731) Pub Date : 2024-03-18 James Muldoon, Callum Cant, Boxi Wu, Mark Graham
This article provides a new typology for understanding human labour integrated into the production of artificial intelligence systems through data preparation and model evaluation. We call these forms of labour ‘AI data work’ and show how they are an important and necessary element of the artificial intelligence production process. We draw on fieldwork with an artificial intelligence data business
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Just public algorithms: Mapping public engagement with the use of algorithms in UK public services Big Data & Society (IF 8.731) Pub Date : 2024-03-18 Helen Pallett, Catherine Price, Jason Chilvers, Simon Burall
This paper proposes and models a novel approach to public engagement with the use of algorithms in public services. Algorithms pose significant risks which need to be anticipated and mitigated through democratic governance, including public engagement. We argue that as the challenge of creating responsible algorithms within a dynamic innovation system is one that will never definitively be accomplished
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Participatory action research in critical data studies: Interrogating AI from a South–North approach Big Data & Society (IF 8.731) Pub Date : 2024-03-18 Andrea Medrado, Pieter Verdegem
In this article, we draw inspiration from participatory action research (PAR) and the work of Latin American thinkers such as Freire and Fals Borda to interrogate artificial intelligence (AI). We propose a South-North flow by utilising PAR approaches that stem from Latin America, challenging how the North's centrality is taken for granted regarding AI epistemologies, experiences, and understandings
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Big AI: Cloud infrastructure dependence and the industrialisation of artificial intelligence Big Data & Society (IF 8.731) Pub Date : 2024-03-12 Fernando van der Vlist, Anne Helmond, Fabian Ferrari
Critical scholars contend that ‘There is no AI without Big Tech’. This study delves into the substantial role played by major technology conglomerates, including Amazon, Microsoft, and Google (Alphabet), in the ‘industrialisation of artificial intelligence’. This concept encapsulates the shift of AI technologies from the research and development stage to practical, real-world applications across diverse
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Reactionary sensemaking: Mapping the micropolitics of online oppositional subcultures Big Data & Society (IF 8.731) Pub Date : 2024-03-08 Marc Tuters, Melody Devries, Tommaso Venturini, Daniël de Zeeuw, Tom Willaert
Internet memes used to be funny, but somewhere in the mid-2010's, a darker dimension surfaced. This editorial explores this ‘reactionary turn’ in digital culture through a collection of articles and commentaries on ‘the micropolitics of online oppositional subcultures’. In the special theme, these range from commentaries on how misogyny and hate speech exploit platform affordances to articles tracing
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Critical data studies with Latin America: Theorizing beyond data colonialism Big Data & Society (IF 8.731) Pub Date : 2024-02-26 Jonas C. L. Valente, Rafael Grohmann
The article aims to theorize about critical data studies with Latin America beyond the framework of data colonialism, arguing that the long history of social thought in the region can contribute to a more nuanced understanding of the datafication. It discusses views around dependence, oppressions, and liberation, debating how Latin American authors can be useful for current critical data studies, in
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Controversies, contradiction, and “participation” in AI Big Data & Society (IF 8.731) Pub Date : 2024-02-26 Mona Sloane
This commentary examines the inherent contradictions between participation in artificial intelligence (AI), controversy studies, and AI narratives.
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Prediction and explainability in AI: Striking a new balance? Big Data & Society (IF 8.731) Pub Date : 2024-02-26 Aviad Raz, Bert Heinrichs, Netta Avnoon, Gil Eyal, Yael Inbar
The debate regarding prediction and explainability in artificial intelligence (AI) centers around the trade-off between achieving high-performance accurate models and the ability to understand and interpret the decisionmaking process of those models. In recent years, this debate has gained significant attention due to the increasing adoption of AI systems in various domains, including healthcare, finance
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Stabilizing translucencies: Governing AI transparency by standardization Big Data & Society (IF 8.731) Pub Date : 2024-02-26 Charlotte Högberg
Standards are put forward as important means to turn the ideals of ethical and responsible artificial intelligence into practice. One principle targeted for standardization is transparency. This article attends to the tension between standardization and transparency, by combining a theoretical exploration of these concepts with an empirical analysis of standardizations of artificial intelligence transparency
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Harvesting value: Corporate strategies of data assetization in agriculture and their socio-ecological implications Big Data & Society (IF 8.731) Pub Date : 2024-02-26 Sarah Hackfort, Sarah Marquis, Kelly Bronson
The global food system is characterized by market concentration and oligopoly. In our article, we focus on the most powerful input supply and machinery companies and analyze how these firms create value, both economic and otherwise, from big data. In digital capitalism, data is valorized across sectors; personal data is aggregated into large-scale datasets, a practice that feeds economic concentration
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Situating data relations in the datafied home: A methodological approach Big Data & Society (IF 8.731) Pub Date : 2024-02-26 Gaia Amadori, Giovanna Mascheroni
Studying datafication focusing on the microlevel of everyday life poses epistemological and methodological challenges. Indeed, the black-boxed nature of algorithms makes data inaccessible and unintelligible to the researcher. Therefore, this paper aims to advance a methodological proposal for addressing the situatedness of datafication in everyday life by framing mediatised relations as a proxy for
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Super SDKs: Tracking personal data and platform monopolies in the mobile Big Data & Society (IF 8.731) Pub Date : 2024-02-21 Jennifer Pybus, Mark Coté
In this article we address the question ‘what is tracking in the mobile ecosystem’ through a comprehensive overview of the Software Development Kit (SDK). Our research reveals a complex infrastructural role for these technical objects connecting end-user data with app developers, third parties and dominant advertising platforms like Google and Facebook. We present an innovative theoretical framework
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Inequalities in privacy cynicism: An intersectional analysis of agency constraints Big Data & Society (IF 8.731) Pub Date : 2024-02-16 Christian Pieter Hoffmann, Christoph Lutz, Giulia Ranzini
A growing body of research highlights a trend toward widespread attitudes of privacy cynicism, apathy and resignation among Internet users. In this work, we extend these discussions by concentrating on the concept of user agency. Specifically, we examine how five types of structural constraints—interpersonal, cultural, technological, economic and political—restrict user agency and contribute to the
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Cyborgs for strategic communication on social media Big Data & Society (IF 8.731) Pub Date : 2024-02-15 Lynnette Hui Xian Ng, Dawn C Robertson, Kathleen M Carley
Social media platforms are a key ground of information consumption and dissemination. Key figures like politicians, celebrities, and activists have leveraged on its wide user base for strategic communication. Strategic communications, or StratCom, is the deliberate act of information creation and distribution. Its techniques are used by key figures for establishing brand and amplifying messages. Automated
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Synthetic data protection: Towards a paradigm change in data regulation? Big Data & Society (IF 8.731) Pub Date : 2024-02-15 Ana Beduschi
Synthetic data generated through machine learning algorithms from original real-world data is gaining prominence across sectors due to their potential to provide privacy-preserving alternatives to traditional data sources. However, recent studies have raised concerns about the re-identification risks of synthetic data. This article examines the legal challenges surrounding synthetic data protection
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Rethinking the filter bubble? Developing a research agenda for the protective filter bubble Big Data & Society (IF 8.731) Pub Date : 2024-02-09 Jacob Erickson
Filter bubbles and echo chambers have received global attention from scholars, media organizations, and the general public. Filter bubbles have primarily been regarded as intrinsically negative, and many studies have sought to minimize their influence. The detrimental influence of filter bubbles is well-studied. Filter bubbles may, for example, create information silos, amplify misinformation, and
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Algorithmic governmentality in Latin America: Sociotechnical imaginaries, neocolonial soft power, and authoritarianism Big Data & Society (IF 8.731) Pub Date : 2024-02-07 Paola Ricaurte, Edgar Gómez-Cruz, Ignacio Siles
Latin America stands as one of the most unequal regions globally, where economic and social crises persist regardless of the ideological leanings of the ruling governments. Many countries in the region grapple with pervasive issues such as corruption, impunity, and a lack of adherence to the rule of law. In this context of generalized crisis, governments have turned to discourses of innovation and
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Rethinking use-restricted open-source licenses for regulating abuse of generative models Big Data & Society (IF 8.731) Pub Date : 2024-02-05 Jonathan Cui, David A Araujo
The rapid progress of Artificial intelligence in generative modeling is marred by widespread misuse. In response, researchers turn to use-based restrictions—contractual terms prohibiting certain uses—as a “solution” for abuse. While these restrictions can be beneficial to artificial intelligence governance in API-gated settings, their failings are especially significant in open-source models: not only
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Algorithmic decision-making: The right to explanation and the significance of stakes Big Data & Society (IF 8.731) Pub Date : 2024-01-31 Lauritz Aastrup Munch, Jens Christian Bjerring, Jakob Thrane Mainz
The stakes associated with an algorithmic decision are often said to play a role in determining whether the decision engenders a right to an explanation. More specifically, “high stakes” decisions are often said to engender such a right to explanation whereas “low stakes” or “non-high” stakes decisions do not. While the overall gist of these ideas is clear enough, the details are lacking. In this paper
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After the algorithms: A study of meta-algorithmic judgments and diversity in the hiring process at a large multisite company Big Data & Society (IF 8.731) Pub Date : 2024-01-31 Moa Bursell, Lambros Roumbanis
In recent years, both private and public organizations across contexts have begun implementing AI technologies in their recruitment processes. This transition is typically justified by improved efficiency as well as more objective, performance-based ranking, and inclusive selection of job candidates. However, this rapid development has also raised concerns that the use of these emerging technologies
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Health in data space: Formative and experiential dimensions of cross-border health data sharing Big Data & Society (IF 8.731) Pub Date : 2024-01-16 Klaus Hoeyer, Sara Green, Andrea Martani, Alexandra Middleton, Clémence Pinel
Healthcare is increasingly datafied, and a wide range of actors—patients, clinicians, administrators, policymakers, and industry lobbyists—want to be able to exchange and access health data internationally and use them for an increasing number of purposes. Therefore, competing initiatives aimed at fostering international data integration proliferate, with the proposed European Health Data Space as
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Tech workers’ perspectives on ethical issues in AI development: Foregrounding feminist approaches Big Data & Society (IF 8.731) Pub Date : 2024-01-09 Jude Browne, Eleanor Drage, Kerry McInerney
While tech workers are essential stakeholders in ethical artificial intelligence (AI) development and deployment, they are rarely consulted about their understanding of the development of ethical AI. In light of this, we present the findings of our 2020 to 2021 empirical research study in which we collected data from tech workers in a major AI company to better understand what they consider to be the
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A feeling for the algorithm: Diversity, expertise, and artificial intelligence Big Data & Society (IF 8.731) Pub Date : 2024-01-09 Catherine Stinson, Sofie Vlaad
Diversity is often announced as a solution to ethical problems in artificial intelligence (AI), but what exactly is meant by diversity and how it can solve those problems is seldom spelled out. This lack of clarity is one hurdle to motivating diversity in AI. Another hurdle is that while the most common perceptions about what diversity is are too weak to do the work set out for them, stronger notions
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Computational reparations as generative justice: Decolonial transitions to unalienated circular value flow Big Data & Society (IF 8.731) Pub Date : 2024-01-09 Ron Eglash, Kwame P Robinson, Audrey Bennett, Lionel Robert, Mathew Garvin
The Latin roots of the word reparations are “re” (again) plus “parere” which means “to give birth to, bring into being, produce”. Together they mean “to make generative once again”. In this sense, the extraction processes that cause labor injustice, ecological devastation, and social degradation cannot be repaired by simply transferring money. Reparations need to take on the full sense of “restorative”:
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Ethical scaling for content moderation: Extreme speech and the (in)significance of artificial intelligence Big Data & Society (IF 8.731) Pub Date : 2023-05-08 Sahana Udupa, Antonis Maronikolakis, Axel Wisiorek
In this article, we present new empirical evidence to demonstrate the severe limitations of existing machine learning content moderation methods to keep pace with, let alone stay ahead of, hateful ...
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Prediction as extraction of discretion Big Data & Society (IF 8.731) Pub Date : 2023-05-08 Sun-ha Hong
I argue that prediction is not primarily a technological means for knowing future outcomes, but a social model for extracting and concentrating discretionary power. Prediction is a ‘relational gram...
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‘I’ve left enough data’: Relations between people and data and the production of surveillance Big Data & Society (IF 8.731) Pub Date : 2023-05-09 Hwankyung Janet Lee
Exploring emergent relations between data-producing individuals and their data products, this study aims to contribute to the ongoing scholarly discussion on agencies in data practices. It focuses ...
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Stepping back from Data and AI for Good – current trends and ways forward Big Data & Society (IF 8.731) Pub Date : 2023-05-09 Ville Aula, James Bowles
Various ‘Data for Good’ and ‘AI for Good’ initiatives have emerged in recent years to promote and organise efforts to use new computational techniques to solve societal problems. The initiatives ex...
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Modeling COVID-19 with big mobility data: Surveillance and reaffirming the people in the data Big Data & Society (IF 8.731) Pub Date : 2023-05-09 Thomas Walsh
To better understand the COVID-19 pandemic, public health researchers turned to “big mobility data”—location data collected from mobile devices by companies engaged in surveillance capitalism. Publ...
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FAIR data sharing: An international perspective on why medical researchers are lagging behind Big Data & Society (IF 8.731) Pub Date : 2023-05-04 Linda Rainey, Jennifer E Lutomski, Mireille JM Broeders
FAIR data, that is, Findable, Accessible, Interoperable, and Reusable data, and Big Data intersect across issues related to data storage, access, and processing. The solution-oriented FAIR principl...
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Deleterious consequences: How Google's original sociotechnical affordances ultimately shaped ‘trusted users’ in surveillance capitalism Big Data & Society (IF 8.731) Pub Date : 2023-05-01 Renée Ridgway
Google dominates around 92% of the search market worldwide (as of November 2022), with most of its revenue derived from search advertising. However, Google's hegemony over search and the resulting ...
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Big ideas, small data: Opportunities and challenges for data science and the social services sector Big Data & Society (IF 8.731) Pub Date : 2023-05-01 Geri Louise Dimas, Lauri Goldkind, Renata Konrad
The social services sector, comprised of a constellation of programs meeting critical human needs, lacks the resources and infrastructure to implement data science tools. As the use of data science...
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Extrapolation and AI transparency: Why machine learning models should reveal when they make decisions beyond their training Big Data & Society (IF 8.731) Pub Date : 2023-04-21 Xuenan Cao, Roozbeh Yousefzadeh
The right to artificial intelligence (AI) explainability has consolidated as a consensus in the research community and policy-making. However, a key component of explainability has been missing: ex...
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Organic online politics: Farmers, Facebook, and Myanmar's military coup Big Data & Society (IF 8.731) Pub Date : 2023-04-16 Hilary Oliva Faxon, Kendra Kintzi, Van Tran, Kay Zak Wine, Swan Ye Htut
Despite perennial hope in the democratic possibilities of the internet, the rise of digital authoritarianism threatens online and offline freedom across much of the world. Yet while critical data s...
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Predictive privacy: Collective data protection in the context of artificial intelligence and big data Big Data & Society (IF 8.731) Pub Date : 2023-04-16 Rainer Mühlhoff
Big data and artificial intelligence pose a new challenge for data protection as these techniques allow predictions to be made about third parties based on the anonymous data of many people. Exampl...
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Recording the ethical provenance of data and automating data stewardship Big Data & Society (IF 8.731) Pub Date : 2023-04-16 Alexander Bernier, Maili Raven-Adams, Davide Zaccagnini, Bartha M. Knoppers
Health organisations use numerous different mechanisms to collect biomedical data, to determine the applicable ethical, legal and institutional conditions of use, and to reutilise the data in accor...
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The importance of algorithm skills for informed Internet use Big Data & Society (IF 8.731) Pub Date : 2023-04-12 Jonathan Gruber, Eszter Hargittai
Using the Internet means encountering algorithmic processes that influence what information a user sees or hears. Existing research has shown that people's algorithm skills vary considerably, that ...
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Machine learning, meaning making: On reading computer science texts Big Data & Society (IF 8.731) Pub Date : 2023-03-30 Louise Amoore, Alexander Campolo, Benjamin Jacobsen, Ludovico Rella
Computer science tends to foreclose the reading of its texts by social science and humanities scholars – via code and scale, mathematics, black box opacities, secret or proprietary models. Yet, whe...
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“Too Soon” to count? How gender and race cloud notability considerations on Wikipedia Big Data & Society (IF 8.731) Pub Date : 2023-03-29 Mackenzie Emily Lemieux, Rebecca Zhang, Francesca Tripodi
While research has explored the extent of gender bias and the barriers to women's inclusion on English-language Wikipedia, very little research has focused on the problem of racial bias within the ...
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Coloniality and frictions: Data-driven humanitarianism in North-Eastern Nigeria and South Sudan Big Data & Society (IF 8.731) Pub Date : 2023-03-29 Vicki Squire, Modesta Alozie
It is now over a decade since the proclamation of a humanitarian ‘data revolution’, with the rise of ‘innovation’ and the proliferation of ‘data solutions’ rendering data-based humanitarianism an i...
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When research is the context: Cross-platform user expectations for social media data reuse Big Data & Society (IF 8.731) Pub Date : 2023-03-28 Sarah Gilbert, Katie Shilton, Jessica Vitak
Social media provides unique opportunities for researchers to learn about a variety of phenomena—it is often publicly available, highly accessible, and affords more naturalistic observation. Howeve...
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‘I started seeing shadows everywhere’: The diverse chilling effects of surveillance in Zimbabwe Big Data & Society (IF 8.731) Pub Date : 2023-03-21 Amy Stevens, Pete Fussey, Daragh Murray, Kuda Hove, Otto Sake
Recent years have witnessed growing ubiquity and potency of state surveillance measures with heightened implications for human rights and social justice. While impacts of surveillance are routinely...
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Imaginaries of better administration: Renegotiating the relationship between citizens and digital public power Big Data & Society (IF 8.731) Pub Date : 2023-03-20 Terhi Esko, Riikka Koulu
This article investigates future visions of digital public administration as they appear within a particular regulatory process that aims to enable automated decision-making (ADM) in public adminis...
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Smart corruption: Satirical strategies for gaming accountability Big Data & Society (IF 8.731) Pub Date : 2023-03-20 Ritwick Ghosh, Hilary Oliva Faxon
Although new forms of data can be used to hold power to account, they also grant the powerful new resources to game accountability. We dub the latter behavior “smart corruption.” The concept highli...
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Not so fast! Data temporalities in law enforcement and border control Big Data & Society (IF 8.731) Pub Date : 2023-03-20 Matthias Leese, Silvan Pollozek
In this paper, we investigate the temporal implications of data in law enforcement and border control. We start from the assumption that the velocity of knowledge and action is defined by heterogen...
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Fact signalling and fact nostalgia in the data-driven society Big Data & Society (IF 8.731) Pub Date : 2023-03-20 Sun-ha Hong
Post-truth tells the story of a public descending into unreason, aided and abetted by platforms and other data-driven systems. But this apparent collapse of epistemic consensus is, I argue, also do...
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On samples, data, and their mobility in biobanking: How imagined travels help to relate samples and data Big Data & Society (IF 8.731) Pub Date : 2023-03-20 Ingrid Metzler, Lisa-Maria Ferent, Ulrike Felt
Biobanking involves the assembling, curating, and distributing of samples and data. While relations between samples and data are often taken as defining properties of biobanking, several studies ha...
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Virtual state, where are you? A literature review, framework and agenda for failed digital transformation Big Data & Society (IF 8.731) Pub Date : 2023-03-14 Shirley Kempeneer, Frederik Heylen
The users, sensors and networks of the Internet of Things generate huge amounts of data. Given the sophisticated (artificially intelligent) algorithms, computing power and software available, we wo...
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Based and confused: Tracing the political connotations of a memetic phrase across the web Big Data & Society (IF 8.731) Pub Date : 2023-03-14 Sal Hagen, Daniël de Zeeuw
Current research on the weaponisation of far-right discourse online has mostly focused on the dangers of normalising hate speech. However, this often operates on questionable assumptions about how ...
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European Search? How to counter-imagine and counteract hegemonic search with European search engine projects Big Data & Society (IF 8.731) Pub Date : 2023-03-14 Astrid Mager
This article investigates how developers of alternative search engines challenge increasingly corporate imaginaries of digital futures by building out counter-imaginaries of search engines devoted ...