Data Mining in Scientometrics: Usage Analysis for Academic Publications

Olesya Mryglod, Yurij Holovatch, Ralph Kenna

    Research output: Chapter in Book/Report/Conference proceedingConference proceedingpeer-review

    4 Citations (Scopus)

    Abstract

    We perform a statistical analysis of scientific-publication data with a goal to provide quantitative analysis of scientific process. Such an investigation belongs to the newly established field of scientometrics: A branch of the general science of science that covers all quantitative methods to analyze science and research process. As a case study we consider download and citation statistics of the journal 'Europhysics Letters' (EPL), as Europe's flagship letters journal of broad interest to the physics community. While citations are usually considered as an indicator of academic impact, downloads reflect rather the level of attractiveness or popularity of a publication. We discuss peculiarities of both processes and correlations between them.

    Original languageEnglish
    Title of host publicationProceedings of the 2018 IEEE 2nd International Conference on Data Stream Mining and Processing, DSMP 2018
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages241-246
    Number of pages6
    ISBN (Electronic)9781538628744
    DOIs
    Publication statusPublished - 1 Oct 2018
    Event2nd IEEE International Conference on Data Stream Mining and Processing - Lviv, Ukraine
    Duration: 21 Aug 201825 Aug 2018
    Conference number: 2

    Publication series

    NameProceedings of the 2018 IEEE 2nd International Conference on Data Stream Mining and Processing, DSMP 2018

    Conference

    Conference2nd IEEE International Conference on Data Stream Mining and Processing
    Abbreviated titleDSMP 2018
    CountryUkraine
    CityLviv
    Period21/08/1825/08/18

    Keywords

    • citation analysis
    • data analysis
    • scientometrics
    • usage metrics

    ASJC Scopus subject areas

    • Hardware and Architecture
    • Information Systems
    • Signal Processing
    • Information Systems and Management

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