人工知能学会論文誌
Online ISSN : 1346-8030
Print ISSN : 1346-0714
ISSN-L : 1346-0714
原著論文
情報拡散に影響するネットワーク構造特徴
臼井 翔平鳥海 不二夫
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ジャーナル フリー

2015 年 30 巻 1 号 p. 195-203

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抄録

We analyze information diffusion by focusing on network structures. First, we propose a network growth model that produces networks with features required for analysis and perform a validation experiment using Twitter networks. The proposed model produces networks with features calculated from these real networks with high accuracy. Using this proposed model, we produce several networks that exhibit various features. We simulate information diffusion on these networks using an independent cascade (IC) model and calculate the Ability of Information Diffusion (AID). Second, we analyze how each feature affects information diffusion using this simulation. We found that the AID score was affected by the average shortest-path length L and variance of closeness centrality σι. We got a high AID score by a network with low L and σι.

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© 人工知能学会 2015
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