| Project/Area Number |
24300064
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Partial Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | National Institute of Advanced Industrial Science and Technology |
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Principal Investigator |
ITSUKI Noda 独立行政法人産業技術総合研究所, 人間情報研究部門, 総括研究主幹 (40357744)
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| Co-Investigator(Kenkyū-buntansha) |
TORIUMI Fujio 東京大学, 工学(系)研究科(研究院), 准教授 (30377775)
KURIHARA Satoshi 電気通信大学, その他の研究科, 教授 (30397658)
YAMASHITA Tomohisa 独立行政法人産業技術総合研究所, 人間情報研究部門, 主任研究員 (50415759)
KAZAMA Kazuhiro 和歌山大学, システム工学部, 教授 (60647204)
SHINODA Kosuke 電気通信大学, その他の研究科, 助教 (90533191)
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| Project Period (FY) |
2012-04-01 – 2015-03-31
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| Project Status |
Completed (Fiscal Year 2014)
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| Budget Amount *help |
¥18,070,000 (Direct Cost: ¥13,900,000、Indirect Cost: ¥4,170,000)
Fiscal Year 2014: ¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
Fiscal Year 2013: ¥6,370,000 (Direct Cost: ¥4,900,000、Indirect Cost: ¥1,470,000)
Fiscal Year 2012: ¥8,060,000 (Direct Cost: ¥6,200,000、Indirect Cost: ¥1,860,000)
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| Keywords | 災害情報システム / 社会シミュレーション / マルチエージェント学習 / ソーシャルメディア / 情報伝搬 / 資源共有 / マルチエージェント / 災害情報共有 / 社会的混乱 / レジリエンス / SNS / 社会ネットワーク / 知的エージェント / 情報工学 / 防災 / 人工知能 / 認知科学 |
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| Outline of Final Research Achievements |
We analyzed what the Social Media are being using in a time of earthquake disaster from a tweets archive in the Great East Japan Earthquakes. Based on these analyses, we studied models of network generation and information flow for replication of such a processes of an information diffusion. In addition, we clarify suitable network structures for information sharing by analyzing social media data of twitter at the moment of the great east japan earth quake. We also studied extraction and visualization methods of discussion about events such as earthquakes and nuclear accidents from a tweet archive in the Great East Japan Earthquake. On the other hand, we modeled people’s behaviors on Social Media as a game of resource selection by multi-agent, and investigate relations of agents behaviors and total optimality of communities.
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