An Analysis of Characteristics of Student-Athletes from Questionnaire by SVM

Toru Sugihara, Soichiro Aihara, Sachio Hirokawa, Takashi Nara

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

    Abstract

    What sort of care should a university take for student-athletes? To answer the question and to consider the future educational strategy are one of big issues for many universities. The authors created a questionnaire which consists of 77 questions with multiple choice form. We collected the responses from 100 student-athletes and 141 other students. The present paper analyzed the characteristic features of student-athletes. We considered 312 kinds of combination of question items and the response choices as words and the questionnaire record of a student as a document written in those words. Then we applied the text mining method SVM (support vector machine) and feature selection. As the result, we confirmed that we can distinguish student-athletes from other students with 90% accuracy based on 16 characteristic features such as (a) they spend much time on athlete club and not on study, (b) they want to work for economically rich life, (c) they think that it is advantageous to job hunting or graduate school if they have good grades and (d) they have less interests on international perspective in campus life.

    Original languageEnglish
    Title of host publicationProceedings - 2017 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017
    EditorsKiyota Hashimoto, Naoki Fukuta, Tokuro Matsuo, Sachio Hirokawa, Masao Mori, Masao Mori
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages163-166
    Number of pages4
    ISBN (Electronic)9781538606216
    DOIs
    Publication statusPublished - Nov 15 2017
    Event6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017 - Hamamatsu, Shizuoka, Japan
    Duration: Jul 9 2017 → …

    Publication series

    NameProceedings - 2017 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017

    Other

    Other6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017
    CountryJapan
    CityHamamatsu, Shizuoka
    Period7/9/17 → …

    All Science Journal Classification (ASJC) codes

    • Artificial Intelligence
    • Computer Networks and Communications
    • Computer Science Applications
    • Information Systems
    • Information Systems and Management

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