Modeling continuous-time information diffusion process on complex networks
| Project/Area Number |
20500147
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | Ryukoku University |
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Principal Investigator |
KIMURA Masahiro Ryukoku University, 理工学部, 教授 (10396153)
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| Co-Investigator(Kenkyū-buntansha) |
NAKANO Ryohei 中部大学, 工学部, 教授 (90324467)
SAITO Kazumi 静岡県立大学, 経営情報学部, 教授 (80379544)
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| Project Period (FY) |
2008 – 2010
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| Project Status |
Completed (Fiscal Year 2010)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2010: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2009: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2008: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | 社会ネットワーク分析 / 情報拡散モデル / 機械学習 / 影響最大化 / 汚染最小化 / 行動データ分析 / データマイニング / 複雑ネットワーク科学 / 学習アルゴリズム / モデル選択 / トピック伝搬分析 / 意見形成 / SIR型情報拡散モデル / 汚染拡散最小化 / 影響拡散最大化 / SIS型情報拡散モデル / 情報拡散可視化 / トピック抽出 |
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| Research Abstract |
A social network can play an important role as a medium for the spread of various types of information, including innovation, hot topics and even malicious rumors. In this research, we have constructed predictable models for information diffusion phenomena in complex networks by exploiting a machine learning approach. Moreover, we have proposed and evaluated such a variety of applications of the models that present the methods of increasing and decreasing the information spread under given constraints, and analyzing behaviors of nodes in information propagation.
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Report
(4 results)
Research Products
(98 results)
