Allotaxonometry and rank-turbulence divergence: a universal instrument for comparing complex systems
Abstract Complex systems often comprise many kinds of components which vary over many orders of magnitude in size: Populations of cities in countries, individual and corporate wealth in economies, species abundance in ecologies, word frequency in natural language, and node degree in c...
| Автори: | , , , , , , , , , |
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| Інші автори: | |
| Формат: | Стаття |
| Мова: | English |
| Опубліковано: |
Springer Berlin Heidelberg
2023
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| Онлайн доступ: | https://hdl.handle.net/1721.1/152386 |
| _version_ | 1826198553363480576 |
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| author | Dodds, Peter S. Minot, Joshua R. Arnold, Michael V. Alshaabi, Thayer Adams, Jane L. Dewhurst, David R. Gray, Tyler J. Frank, Morgan R. Reagan, Andrew J. Danforth, Christopher M. |
| author2 | Massachusetts Institute of Technology. Institute for Data, Systems, and Society |
| author_facet | Massachusetts Institute of Technology. Institute for Data, Systems, and Society Dodds, Peter S. Minot, Joshua R. Arnold, Michael V. Alshaabi, Thayer Adams, Jane L. Dewhurst, David R. Gray, Tyler J. Frank, Morgan R. Reagan, Andrew J. Danforth, Christopher M. |
| author_sort | Dodds, Peter S. |
| collection | MIT |
| description | Abstract
Complex systems often comprise many kinds of components which vary over many orders of magnitude in size: Populations of cities in countries, individual and corporate wealth in economies, species abundance in ecologies, word frequency in natural language, and node degree in complex networks. Here, we introduce ‘allotaxonometry’ along with ‘rank-turbulence divergence’ (RTD), a tunable instrument for comparing any two ranked lists of components. We analytically develop our rank-based divergence in a series of steps, and then establish a rank-based allotaxonograph which pairs a map-like histogram for rank-rank pairs with an ordered list of components according to divergence contribution. We explore the performance of rank-turbulence divergence, which we view as an instrument of ‘type calculus’, for a series of distinct settings including: Language use on Twitter and in books, species abundance, baby name popularity, market capitalization, performance in sports, mortality causes, and job titles. We provide a series of supplementary flipbooks which demonstrate the tunability and storytelling power of rank-based allotaxonometry. |
| first_indexed | 2024-09-23T11:06:41Z |
| format | Article |
| id | mit-1721.1/152386 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T11:06:41Z |
| publishDate | 2023 |
| publisher | Springer Berlin Heidelberg |
| record_format | dspace |
| spelling | mit-1721.1/1523862024-02-05T18:30:04Z Allotaxonometry and rank-turbulence divergence: a universal instrument for comparing complex systems Dodds, Peter S. Minot, Joshua R. Arnold, Michael V. Alshaabi, Thayer Adams, Jane L. Dewhurst, David R. Gray, Tyler J. Frank, Morgan R. Reagan, Andrew J. Danforth, Christopher M. Massachusetts Institute of Technology. Institute for Data, Systems, and Society Abstract Complex systems often comprise many kinds of components which vary over many orders of magnitude in size: Populations of cities in countries, individual and corporate wealth in economies, species abundance in ecologies, word frequency in natural language, and node degree in complex networks. Here, we introduce ‘allotaxonometry’ along with ‘rank-turbulence divergence’ (RTD), a tunable instrument for comparing any two ranked lists of components. We analytically develop our rank-based divergence in a series of steps, and then establish a rank-based allotaxonograph which pairs a map-like histogram for rank-rank pairs with an ordered list of components according to divergence contribution. We explore the performance of rank-turbulence divergence, which we view as an instrument of ‘type calculus’, for a series of distinct settings including: Language use on Twitter and in books, species abundance, baby name popularity, market capitalization, performance in sports, mortality causes, and job titles. We provide a series of supplementary flipbooks which demonstrate the tunability and storytelling power of rank-based allotaxonometry. 2023-10-06T15:48:02Z 2023-10-06T15:48:02Z 2023-09-19 2023-09-24T03:14:33Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/152386 EPJ Data Science. 2023 Sep 19;12(1):37 PUBLISHER_CC en https://doi.org/10.1140/epjds/s13688-023-00400-x Creative Commons Attribution https://creativecommons.org/licenses/by/4.0/ Springer-Verlag GmbH, DE application/pdf Springer Berlin Heidelberg Springer Berlin Heidelberg |
| spellingShingle | Dodds, Peter S. Minot, Joshua R. Arnold, Michael V. Alshaabi, Thayer Adams, Jane L. Dewhurst, David R. Gray, Tyler J. Frank, Morgan R. Reagan, Andrew J. Danforth, Christopher M. Allotaxonometry and rank-turbulence divergence: a universal instrument for comparing complex systems |
| title | Allotaxonometry and rank-turbulence divergence: a universal instrument for comparing complex systems |
| title_full | Allotaxonometry and rank-turbulence divergence: a universal instrument for comparing complex systems |
| title_fullStr | Allotaxonometry and rank-turbulence divergence: a universal instrument for comparing complex systems |
| title_full_unstemmed | Allotaxonometry and rank-turbulence divergence: a universal instrument for comparing complex systems |
| title_short | Allotaxonometry and rank-turbulence divergence: a universal instrument for comparing complex systems |
| title_sort | allotaxonometry and rank turbulence divergence a universal instrument for comparing complex systems |
| url | https://hdl.handle.net/1721.1/152386 |
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