Encyclopedia of Big Data

Living Edition
| Editors: Laurie A. Schintler, Connie L. McNeely


Living reference work entry
DOI: https://doi.org/10.1007/978-3-319-32001-4_2-1


We are now living in an “algorithm society.” Indeed, algorithms have become ubiquitous, running behind the scenes everywhere for various purposes, from recommending movies to optimizing autonomous vehicle routing to detecting fraudulent financial transactions. Nevertheless, algorithms are far from new. The idea of an algorithm, referring generally to a set of rules to follow for solving a problem or achieving a goal, goes back thousands of years. However, the use of algorithms has exploded in recent years for a couple of interrelated reasons:
  1. 1.

    Advancements in computational and information processing technologies have made it easier to develop, codify, implement, and execute algorithms.

  2. 2.

    Open-source digital platforms and crowdsourcing projects enable algorithmic code to be shared and disseminated to a large audience.

  3. 3.

    The complexities and nuances of big data create unique computational and analytical challenges, which demand algorithms.

Algorithms used for big data...
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Further Readings

  1. Li, K. C., Jiang, H., Yang, L. T., & Cuzzocrea, A. (Eds.). (2015). Big data: Algorithms, analytics, and applications. Boca Raton: CRC Press.Google Scholar
  2. Mnich, M. (2018). Big data algorithms beyond machine learning. KI – Künstliche Intelligenz, 32(1), 9–17.CrossRefGoogle Scholar
  3. Olhede, S. C., & Wolfe, P. J. (2018). The growing ubiquity of algorithms in society: Implications, impacts and innovations. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 376(2128), 20170364.CrossRefGoogle Scholar
  4. Prabhu, C. S. R., Chivukula, A. S., Mogadala, A., Ghosh, R., & Livingston, L. J. (2019). Big data analytics. In Big data analytics: Systems, algorithms, applications (pp. 1–23). Singapore: Springer.CrossRefGoogle Scholar
  5. Schuilenburg, M., & Peeters, R. (Eds.). (2020). The algorithmic society: Technology, power, and knowledge. London: Routledge.Google Scholar
  6. Siddiqa, A., Hashem, I. A. T., Yaqoob, I., Marjani, M., Shamshirband, S., Gani, A., & Nasaruddin, F. (2016). A survey of big data management: Taxonomy and state-of-the-art. Journal of Network and Computer Applications, 71, 151–166.CrossRefGoogle Scholar
  7. Yu, P. K. (2020). The algorithmic divide and equality in the age of artificial intelligence. Florida Law Review, 72, 19–44.Google Scholar

Authors and Affiliations

  1. 1.Schar School of Policy and GovernmentGeorge Mason UniversityArlingtonUSA