Psychological foundation of human large social networks
| Project/Area Number |
17H07229
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| Research Category |
Grant-in-Aid for Research Activity Start-up
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| Allocation Type | Single-year Grants |
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| Research Field |
Social psychology
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| Research Institution | Aichi Shukutoku University |
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Principal Investigator |
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| Project Period (FY) |
2017-08-25 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Fiscal Year 2018: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2017: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | 社会的ネットワーク / 心の理論 / アンサンブル認知 / 個人差 / コミュニティ / 社会的認知 / 社会性 / 社会的ネットワークサイズ / アンサンブル知覚 / 動機づけ / 社会心理学 |
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| Outline of Final Research Achievements |
This study aimed to understand the psychological underpinnings of human large social networks. First, analyses revealed that individuals’ social networks were structured in several communities, and there were large individual differences. Second, I developed psychological tasks to measure the social cognitive function as a factor to explain the individual differences in social network structures. Furthermore, I examined relationships between the performance of the tasks and social network size and structures. The results suggested that the social cognitive function such as theory-of-mind may not work as the basis of a large-scale social network. However, there were no clear relationships between social cognitive function, such as ensemble perception of crowd’s gaze direction, and social network size and structures.
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| Academic Significance and Societal Importance of the Research Achievements |
大規模な協力社会は人間の大きな特徴である。大規模な社会的ネットワークの心理基盤を明らかにすることは、人間社会の成り立ちの特徴を明らかにするだけでなく、多様性が明示化された現代社会において、他者との「違いを共に生きる」ために重要な検討課題である。従来の研究では、「他者の心を読み取る」認知機能が、大規模な社会的ネットワークの心理基盤と考えられてきたが、本研究の結果は、その想定を支持しないものであった。本研究は、広く受け入れられている理論的な想定を再考するきっかけとなる点で意義がある。
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Report
(3 results)
Research Products
(9 results)
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[Presentation] Chasing stars and confirming alliance: Two effective strategies for learning social network structure2017
Author(s)
Igarashi, T., Kato, J., Shiraki, Y., Hirashima, T., & Tamai, R.
Organizer
The 2nd Australian Social Network Analysis Conference (ASNAC 2017)
Place of Presentation
Charles Perkins Centre （Sydney, Australia）
Year and Date
2017-11-28
Related Report
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