| Project/Area Number |
19K21571
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| Research Category |
Grant-in-Aid for Challenging Research (Exploratory)
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| Allocation Type | Multi-year Fund |
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| Review Section |
A New Phase of Our Advanced Science and Technology Society
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| Research Institution | Waseda University |
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Principal Investigator |
Sayama Hiroki 早稲田大学, 商学学術院, 教授(任期付) (30345425)
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| Project Period (FY) |
2019-06-28 – 2023-03-31
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| Project Status |
Completed (Fiscal Year 2022)
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| Budget Amount *help |
¥6,370,000 (Direct Cost: ¥4,900,000、Indirect Cost: ¥1,470,000)
Fiscal Year 2021: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2020: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2019: ¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
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| Keywords | 意見の極端化 / 社会ネットワーク / 情報通信技術 / 数理モデル化 / 機械学習 / データサイエンス / 複雑系 / 適応的ネットワーク / ideological escalation / adaptive social networks / communication networks / machine learning / data science |
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| Outline of Research at the Start |
The proposed project will develop, and quantitatively validate, a comprehensive adaptive social network model that will include communication intensity and selective attention tendency as the new key variables, and systematically investigate the effects of those variables on ideological dynamics on the social network. The model validation will be conducted by collecting empirical data from social network services and mapping ideological states of users to a metric space using machine learning techniques.
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| Outline of Final Research Achievements |
In today's highly advanced information society, differences in opinions and ideologies are escalating among various members of society with different backgrounds, creating and expanding insurmountable gaps between them. One possible cause for this is the sophistication and acceleration of information communication technology and the improvement of users' ability to select favorite information sources arbitrarily. In this project, we used both a mathematical modeling-based constructive method and a data-driven empirical method to study how advanced information communication technology would affect the extremization of opinions and ideologies in society. As a result, we obtained many useful findings, including the fact that as people's information gathering ability and homophilic tendency increase, social fragmentation and extremization of ideologies and opinions are promoted.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究は，社会ネットワークにおける自然発生的な思想の極端化の機構を数理モデルを用いて理論的に説明し，かつ複数の実データを用いて定量的な実証を行った．プロジェクト全体を通じて，人々の情報収集能力が高度化しかつ同種親和性が強まるにつれ社会分断と思想・意見の極端化が促進されること，極端な意見は関心を集めやすいこと，個人の意見は変遷するが周囲も同様に変遷するので自身の意見の極端化に気づきにくいこと，新規性を指向する挙動や個人間の挙動のばらつきが社会分断を抑制すること，など高度情報化社会における社会の構造・状態の変化を理解するうえで，示唆に富む重要な知見を多数得ることができた．
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