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JournalISSN: 2053-9517

Big Data & Society 

SAGE Publishing
About: Big Data & Society is an academic journal published by SAGE Publishing. The journal publishes majorly in the area(s): Big data & Social media. It has an ISSN identifier of 2053-9517. It is also open access. Over the lifetime, 539 publications have been published receiving 22742 citations. The journal is also known as: Big data and society.

Papers published on a yearly basis

Papers
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Journal ArticleDOI
Rob Kitchin1
TL;DR: The authors examines how the availability of Big Data, coupled with new data analytics, challenges established epistemologies across the sciences, social sciences and humanities, and assesses the extent to which they are engendering paradigm shifts across multiple disciplines.
Abstract: This article examines how the availability of Big Data, coupled with new data analytics, challenges established epistemologies across the sciences, social sciences and humanities, and assesses the extent to which they are engendering paradigm shifts across multiple disciplines. In particular, it critically explores new forms of empiricism that declare ‘the end of theory’, the creation of data-driven rather than knowledge-driven science, and the development of digital humanities and computational social sciences that propose radically different ways to make sense of culture, history, economy and society. It is argued that: (1) Big Data and new data analytics are disruptive innovations which are reconfiguring in many instances how research is conducted; and (2) there is an urgent need for wider critical reflection within the academy on the epistemological implications of the unfolding data revolution, a task that has barely begun to be tackled despite the rapid changes in research practices presently taking place. After critically reviewing emerging epistemological positions, it is contended that a potentially fruitful approach would be the development of a situated, reflexive and contextually nuanced epistemology.

1,463 citations

Journal ArticleDOI
TL;DR: This paper makes three contributions to clarify the ethical importance of algorithmic mediation, including a prescriptive map to organise the debate, and assesses the available literature in order to identify areas requiring further work to develop the ethics of algorithms.
Abstract: In information societies, operations, decisions and choices previously left to humans are increasingly delegated to algorithms, which may advise, if not decide, about how data should be interpreted and what actions should be taken as a result. More and more often, algorithms mediate social processes, business transactions, governmental decisions, and how we perceive, understand, and interact among ourselves and with the environment. Gaps between the design and operation of algorithms and our understanding of their ethical implications can have severe consequences affecting individuals as well as groups and whole societies. This paper makes three contributions to clarify the ethical importance of algorithmic mediation. It provides a prescriptive map to organise the debate. It reviews the current discussion of ethical aspects of algorithms. And it assesses the available literature in order to identify areas requiring further work to develop the ethics of algorithms.

990 citations

Journal ArticleDOI
TL;DR: In this paper, the authors consider the issue of opacity as a problem for socially consequential mechanisms of classification and ranking, such as spam filters, credit card fraud detection, search engines, news, etc.
Abstract: This article considers the issue of opacity as a problem for socially consequential mechanisms of classification and ranking, such as spam filters, credit card fraud detection, search engines, news...

915 citations

Journal ArticleDOI
David Lyon1
TL;DR: Big Data intensifies certain surveillance trends associated with information technology and networks, and is thus implicated in fresh but fluid configurations, and the ethical turn becomes more urgent as a mode of critique.
Abstract: The Snowden revelations about National Security Agency surveillance, starting in 2013, along with the ambiguous complicity of internet companies and the international controversies that followed pr...

513 citations

Journal ArticleDOI
TL;DR: People's lay concepts of algorithmic versus human decisions in a management context are revealed and it is suggested that task characteristics matter in understanding people's experiences with algorithmic technologies.
Abstract: Algorithms increasingly make managerial decisions that people used to make. Perceptions of algorithms, regardless of the algorithms' actual performance, can significantly influence their adoption, ...

478 citations

Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
202350
202262
202186
202084
201946
201843