| Project/Area Number |
18K03451
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 13010:Mathematical physics and fundamental theory of condensed matter physics-related
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| Research Institution | Rissho University (2021-2022)
Niigata University (2018-2020) |
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Principal Investigator |
IYETOMI Hiroshi 立正大学, データサイエンス学部, 教授 (20168090)
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| Project Period (FY) |
2018-04-01 – 2023-03-31
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| Project Status |
Completed (Fiscal Year 2022)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2020: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2019: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2018: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | 有向ネットワーク / 流れ構造 / 階層性 / 循環性 / Helmholtz-Hodge分解 / 蝶ネクタイ構造 / 強連結成分 / サイクル基底 |
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| Outline of Final Research Achievements |
Different flow structures coexist on networks consisting of nodes and directed links connecting them. In this study, we focused on the hierarchy and circularity of flow structures on such directed networks. We developed an integrated analysis tool, FALCON, to incorporate the methods necessary for the network analysis, such as Helmholtz-Hodge decomposition, community extraction, bow-tie decomposition, and visualization based on a spring electrical model. We then applied the obtained analysis methods to several real-world directed network systems that are important for applications (inter-firm relations, trade relations, industrial input-output relations, and stock ownership). In addition, we have applied the methods developed here to the analysis of echo chambers formed in social network services.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究で採用した「世の中に存在する多量の情報をつながり（ネットワーク）の視点から捉える」研究アプローチは，国内外を問わずネットワーク科学として急速に発展している。本研究では有向ネットワークにおける流れ構造の階層性ばかりではなく，その循環性にも焦点をあてている点が，本研究をこれまでの先行研究から差別化した。循環的流れは，貿易関係においては多国間の互恵関係，生産ネットワークでは循環経済，株所有ネットワークでは企業間の循環持ち合い関係，SNSネットワークではエコーチェンバーを表し，本研究で得られた成果は単に学術的な意味があるばかりではなく，社会問題の解決に向けても大いに役立つ。
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