Long tail

An example of a power law graph showing popularity ranking. To the right (yellow) is the long tail; to the left (green) are the few that dominate. In this example, the cutoff is chosen so that areas of both regions are equal.

In statistics and business, a long tail of some distributions of numbers is the portion of the distribution having many occurrences far from the "head" or central part of the distribution. The distribution could involve popularities, random numbers of occurrences of events with various probabilities, etc.[1] The term is often used loosely, with no definition or an arbitrary definition, but precise definitions are possible.

In statistics, the term long-tailed distribution has a narrow technical meaning, and is a subtype of heavy-tailed distribution.[2][3][4] Intuitively, a distribution is (right) long-tailed if, for any fixed amount, when a quantity exceeds a high level, it almost certainly exceeds it by at least that amount: large quantities are probably even larger.[a] Note that there is no sense of the "long tail" of a distribution, but only the property of a distribution being long-tailed.

In business, the term long tail is applied to rank-size distributions or rank-frequency distributions (primarily of popularity), which often form power laws and are thus long-tailed distributions in the statistical sense. This is used to describe the retailing strategy of selling many unique items with relatively small quantities sold of each (the "long tail")—usually in addition to selling fewer popular items in large quantities (the "head"). Sometimes an intermediate category is also included, variously called the body, belly, torso, or middle. The specific cutoff of what part of a distribution is the "long tail" is often arbitrary, but in some cases may be specified objectively; see segmentation of rank-size distributions.

The long tail concept has found some ground for application, research, and experimentation. It is a term used in online business, mass media, micro-finance (Grameen Bank, for example), user-driven innovation (Eric von Hippel), knowledge management, and social network mechanisms (e.g. crowdsourcing, crowdcasting, peer-to-peer), economic models, marketing (viral marketing), and IT Security threat hunting within a SOC (Information security operations center).

  1. ^ Alpheus Bingham and Dwayne Spradlin (2011). The Long Tail of Expertise. Pearson Education. p. 5. ISBN 9780132823135.
  2. ^ Asmussen, S. R. (2003). "Steady-State Properties of GI/G/1". Applied Probability and Queues. Stochastic Modelling and Applied Probability. Vol. 51. pp. 266–301. doi:10.1007/0-387-21525-5_10. ISBN 978-0-387-00211-8.
  3. ^ Levine, David M.; Stephan, David; Krehbiel, Timothy C.; Berenson, Mark L. Statistics for Managers using Microsoft Excel. 3rd edition. Prentice Hall, 2002, p. 124.
  4. ^ John Verzani (2004). Using R for Introductory Statistics. CRC Press. p. 62. ISBN 978-1-58488450-7.


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