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Big Data & Society is a peer-reviewed journal published by SAGE, covering Ethics and Social Impacts of AI, Privacy, Security, and Data Protection, Social Media and Politics. Over its lifetime it has published 1,009 papers, which have received 54,414 citations.
| Publisher | SAGE |
|---|---|
| Reference style | Author–year (Harvard) Author–year — (Smith, 2023) in the text Smith, A., Jones, B. and Lee, C. (2023) 'A representative article title', Big Data & Society, 12(3), pp. 45–58.
Formats any DOI in Big Data & Society style. No sign-up. |
| Publishes research in | Ethics and Social Impacts of AI Privacy, Security, and Data Protection Social Media and Politics Digital Economy and Work Transformation Misinformation and Its Impacts |
| ISSN | 2053-9517 |
| Citation impact (2-yr) | 6.08 |
| h-index | 105 |
| i10-index | 637 |
| Article processing charge | $800 |
| Open access | Yes — indexed in DOAJ |
| Top institutions publishing here | University of Amsterdam |
| Journal website | us.sagepub.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
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…
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 trends, market segmentation and advertising, insurance or loan qualification, and credit scoring. These mechanisms of classification all frequently rely on computational algorithms, and in many cases…
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…
Algorithms increasingly make managerial decisions that people used to make. Perceptions of algorithms, regardless of the algorithms' actual performance, can significantly influence their adoption, yet we do not fully understand how people perceive decisions made by algorithms as compared with decisions made by humans. To explore perceptions of algorithmic management, we conducted an online experiment…
The collection and circulation of data is now a central element of increasingly more sectors of contemporary capitalism. This article analyses data as a form of capital that is distinct from, but has its roots in, economic capital. Data collection is driven by the perpetual cycle of capital accumulation, which in turn drives capital to…
