2019 Hits: Big Data and Society
What did researchers read and cite in 2019?
SAGE MethodSpace features original posts, interviews, and resources about using, developing, teaching, or writing about research methods. As 2019 draws to a close, we're highlighting relevant open access articles that attracted readers' attentions this year.
Big Data & Society (BD&S) is an Open Access peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities and computing and their intersections with the arts and natural sciences about the implications of Big Data for societies.
The Journal's key purpose is to provide a space for connecting debates about the emerging field of Big Data practices and how they are reconfiguring academic, social, industry, business and governmental relations, expertise, methods, concepts and knowledge.
See the Big Data & Society blog for related posts.
Here are references and links for the most read and cited articles. You will note that the most read and cited sources were not necessarily published in 2019.
Most Read (in the last six months of 2019, listed in the order of download popularity)
Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society. https://doi.org/10.1177/2053951716679679
Kitchin, R. (2014). Big Data, new epistemologies and paradigm shifts. Big Data & Society. https://doi.org/10.1177/2053951714528481
Lyon, D. (2014). Surveillance, Snowden, and Big Data: Capacities, consequences, critique. Big Data & Society. https://doi.org/10.1177/2053951714541861
Burrell, J. (2016). How the machine ‘thinks’: Understanding opacity in machine learning algorithms. Big Data & Society. https://doi.org/10.1177/2053951715622512
Zwitter, A. (2014). Big Data ethics. Big Data & Society. https://doi.org/10.1177/2053951714559253
Torabi Asr, F., & Taboada, M. (2019). Big Data and quality data for fake news and misinformation detection. Big Data & Society. https://doi.org/10.1177/2053951719843310
Most Cited (in the last three years)
Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society. https://doi.org/10.1177/2053951716679679
Dourish, P. (2016). Algorithms and their others: Algorithmic culture in context. Big Data & Society. https://doi.org/10.1177/2053951716665128
Iliadis, A., & Russo, F. (2016). Critical data studies: An introduction. Big Data & Society. https://doi.org/10.1177/2053951716674238
Pink, S., Sumartojo, S., Lupton, D., & Heyes La Bond, C. (2017). Mundane data: The routines, contingencies and accomplishments of digital living. Big Data & Society. https://doi.org/10.1177/2053951717700924