Co-citation Network による宗教思想文書の解析  [in Japanese] Co-citation Network Analysis of Religious Texts  [in Japanese]

Access this Article

Search this Article

Author(s)

    • 村井 源 MURAI Hajime
    • 東京工業大学社会理工学研究科価値システム専攻 Department of Value and Decision Science, Graduate School of Decision Science and Technology, Tokyo Institute of Technology
    • 徃住 彰文 TOKOSUMI Akifumi
    • 東京工業大学社会理工学研究科価値システム専攻 Department of Value and Decision Science, Graduate School of Decision Science and Technology, Tokyo Institute of Technology

Abstract

This paper introduces a method of representing in a network the thoughts of individual authors of dogmatic texts numerically and objectively by means of co-citation analysis and a method of distinguishing between the thoughts of various authors by clustering and analysis of clustered elements, generated by the clustering process. Using these methods, this paper creates and analyzes the co-citation networks for five authoritative Christian theologians through history (Augustine, Thomas Aquinas, Jean Calvin, Karl Barth, John Paul II). These analyses were able to extract the core element of Christian thought (Jn 1:14, Ph 2:6, Ph 2:7, Ph 2:8, Ga 4:4), as well as distinctions between the individual theologians in terms of their sect (Catholic or Protestant) and era (thinking about the importance of God's creation and the necessity of spreading the Gospel). By supplementing conventional literary methods in areas such as philosophy and theology, with these numerical and objective methods, it should be possible to compare the characteristics of various doctrines. The ability to numerically and objectively represent the characteristics of various thoughts opens up the possibilities of utilizing new information technology, such as web ontology and the Artificial Intelligence, in order to process information about ideological thoughts in the future.

Journal

  • Transactions of the Japanese Society for Artificial Intelligence

    Transactions of the Japanese Society for Artificial Intelligence 21, 473-481, 2006-11-01

    The Japanese Society for Artificial Intelligence

References:  20

Codes

  • NII Article ID (NAID)
    10022006738
  • NII NACSIS-CAT ID (NCID)
    AA11579226
  • Text Lang
    JPN
  • Article Type
    ART
  • ISSN
    13460714
  • NDL Article ID
    8686564
  • NDL Source Classification
    ZM13(科学技術--科学技術一般--データ処理・計算機)
  • NDL Call No.
    Z74-C589
  • Data Source
    CJP  NDL  J-STAGE 
Page Top