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Wasserman M, Zeng XH, Amaral LA. Cross-evaluation of metrics to estimate the significance of creative works. Proc Natl Acad Sci U S A. 2015;112(5):1281-6doi: 10.1073/pnas.1412198112.
Wasserman, M., Zeng, X. H., & Amaral, L. A. (2015). Cross-evaluation of metrics to estimate the significance of creative works. Proceedings of the National Academy of Sciences of the United States of America, 112(5), 1281-6. https://doi.org/10.1073/pnas.1412198112
Wasserman, Max, et al. "Cross-evaluation of metrics to estimate the significance of creative works." Proceedings of the National Academy of Sciences of the United States of America vol. 112,5 (2015): 1281-6. doi: https://doi.org/10.1073/pnas.1412198112
Wasserman M, Zeng XH, Amaral LA. Cross-evaluation of metrics to estimate the significance of creative works. Proc Natl Acad Sci U S A. 2015 Feb 03;112(5):1281-6. doi: 10.1073/pnas.1412198112. Epub 2015 Jan 20. PMID: 25605881; PMCID: PMC4321294.
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Proc Natl Acad Sci U S A. 2015 Feb 03;112(5):1281-6. doi: 10.1073/pnas.1412198112. Epub 2015 Jan 20.

Cross-evaluation of metrics to estimate the significance of creative works.

Proceedings of the National Academy of Sciences of the United States of America

Max Wasserman, Xiao Han T Zeng, Luís A Nunes Amaral

Affiliations

  1. Departments of Engineering Sciences and Applied Mathematics.
  2. Chemical and Biological Engineering, and.
  3. Chemical and Biological Engineering, and Physics and Astronomy, Howard Hughes Medical Institute, and Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL 60208 [email protected].

PMID: 25605881 PMCID: PMC4321294 DOI: 10.1073/pnas.1412198112

Abstract

In a world overflowing with creative works, it is useful to be able to filter out the unimportant works so that the significant ones can be identified and thereby absorbed. An automated method could provide an objective approach for evaluating the significance of works on a universal scale. However, there have been few attempts at creating such a measure, and there are few "ground truths" for validating the effectiveness of potential metrics for significance. For movies, the US Library of Congress's National Film Registry (NFR) contains American films that are "culturally, historically, or aesthetically significant" as chosen through a careful evaluation and deliberation process. By analyzing a network of citations between 15,425 United States-produced films procured from the Internet Movie Database (IMDb), we obtain several automated metrics for significance. The best of these metrics is able to indicate a film's presence in the NFR at least as well or better than metrics based on aggregated expert opinions or large population surveys. Importantly, automated metrics can easily be applied to older films for which no other rating may be available. Our results may have implications for the evaluation of other creative works such as scientific research.

Keywords: IMDb; citations; complex networks; data science; films

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