A nutritional label for rankings

Ke Yang, Julia Stoyanovich, Abolfazl Asudeh, Bill Howe, H. V. Jagadish, Gerome Miklau

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Algorithmic decisions often result in scoring and ranking individuals to determine credit worthiness, qualifications for college admissions and employment, and compatibility as dating partners. While automatic and seemingly objective, ranking algorithms can discriminate against individuals and protected groups, and exhibit low diversity. Furthermore, ranked results are often unstable-small changes in the input data or in the ranking methodology may lead to drastic changes in the output, making the result uninformative and easy to manipulate. Similar concerns apply in cases where items other than individuals are ranked, including colleges, academic departments, or products. In this demonstration we present Ranking Facts, a Web-based application that generates a "nutritional label" for rankings. Ranking Facts is made up of a collection of visual widgets that implement our latest research results on fairness, stability, and transparency for rankings, and that communicate details of the ranking methodology, or of the output, to the end user. We will showcase Ranking Facts on real datasets from different domains, including college rankings, criminal risk assessment, and financial services.

    Original languageEnglish (US)
    Title of host publicationSIGMOD 2018 - Proceedings of the 2018 International Conference on Management of Data
    EditorsGautam Das, Christopher Jermaine, Ahmed Eldawy, Philip Bernstein
    PublisherAssociation for Computing Machinery
    Pages1773-1776
    Number of pages4
    ISBN (Electronic)9781450317436
    DOIs
    StatePublished - May 27 2018
    Event44th ACM SIGMOD International Conference on Management of Data, SIGMOD 2018 - Houston, United States
    Duration: Jun 10 2018Jun 15 2018

    Other

    Other44th ACM SIGMOD International Conference on Management of Data, SIGMOD 2018
    CountryUnited States
    CityHouston
    Period6/10/186/15/18

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    Risk assessment
    Transparency
    Labels
    Demonstrations

    ASJC Scopus subject areas

    • Software
    • Information Systems

    Cite this

    Yang, K., Stoyanovich, J., Asudeh, A., Howe, B., Jagadish, H. V., & Miklau, G. (2018). A nutritional label for rankings. In G. Das, C. Jermaine, A. Eldawy, & P. Bernstein (Eds.), SIGMOD 2018 - Proceedings of the 2018 International Conference on Management of Data (pp. 1773-1776). Association for Computing Machinery. https://doi.org/10.1145/3183713.3193568

    A nutritional label for rankings. / Yang, Ke; Stoyanovich, Julia; Asudeh, Abolfazl; Howe, Bill; Jagadish, H. V.; Miklau, Gerome.

    SIGMOD 2018 - Proceedings of the 2018 International Conference on Management of Data. ed. / Gautam Das; Christopher Jermaine; Ahmed Eldawy; Philip Bernstein. Association for Computing Machinery, 2018. p. 1773-1776.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Yang, K, Stoyanovich, J, Asudeh, A, Howe, B, Jagadish, HV & Miklau, G 2018, A nutritional label for rankings. in G Das, C Jermaine, A Eldawy & P Bernstein (eds), SIGMOD 2018 - Proceedings of the 2018 International Conference on Management of Data. Association for Computing Machinery, pp. 1773-1776, 44th ACM SIGMOD International Conference on Management of Data, SIGMOD 2018, Houston, United States, 6/10/18. https://doi.org/10.1145/3183713.3193568
    Yang K, Stoyanovich J, Asudeh A, Howe B, Jagadish HV, Miklau G. A nutritional label for rankings. In Das G, Jermaine C, Eldawy A, Bernstein P, editors, SIGMOD 2018 - Proceedings of the 2018 International Conference on Management of Data. Association for Computing Machinery. 2018. p. 1773-1776 https://doi.org/10.1145/3183713.3193568
    Yang, Ke ; Stoyanovich, Julia ; Asudeh, Abolfazl ; Howe, Bill ; Jagadish, H. V. ; Miklau, Gerome. / A nutritional label for rankings. SIGMOD 2018 - Proceedings of the 2018 International Conference on Management of Data. editor / Gautam Das ; Christopher Jermaine ; Ahmed Eldawy ; Philip Bernstein. Association for Computing Machinery, 2018. pp. 1773-1776
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