社群網路對數成長模型

隨著Web 2.0技術的發展，許多社群網路(如: Facebook, Twitter, 與Digg等)蓬勃發展，了解這些社群網站的成長模型與結構特徵，不但有助於提升經營網站的技術，亦可增進網站的價值，以及更有效地計劃與執行管理策略。因此，在本篇論文中，我們利用網站外部與內部吸引力，提出了社群網站的對數成長模型，來描述社群網站的成長模式與分析其網路特徵。本篇論文可分為三個部份。首先，我們利用網站外部與內部吸引力，提出一個社群網站成長模型；接著，分析模型的特性，並証明所提出的模型具無尺度網路的特徵；最後，我們利用真實社群網站的資料評估所提出的模型，結果顯示，我們所提出的模型可解釋真實世界的社群網站的成長模式及結構特徵，並藉由此模型提出管理上的應用與策略，以提升社群網站的價值。

關鍵字

社群網路；成長模型；無尺度網路；對數成長模型

並列摘要

With advance of Web 2.0 technology, many social networks such as Facebook, Twitter, and Digg, have been highly developed in recent years. Understanding the growth patterns and the characteristics of social networks helps us to promote the technology of running social networks, increase the networks’ value, and formulate marketing and pricing strategies. Therefore, in this thesis, we first utilize the concept of internal and external attractions to propose a population growth model. Next, we analyze the properties of the proposed model and show that the model has the characteristics of sale-free networks. Finally, we collect the data from two real world social networks to evaluate the proposed model. The experimental results show that these two social networks can be well fitted by the proposed model. Furthermore, we address the management implications of the proposed model and discuss how to promote the value of social networks.

並列關鍵字

Social network ； growth model ； scale-free network ； logistic growth model

參考文獻

B.N. Adam, Interaction theory and the social network, Sociometry, Vol. 30, 1967, pp. 64-78.

A.L. Baraba ́si, R. Albert, Emergence of scaling in random networks, Science, Vol. 286, 1999, pp. 509-512.

A.L. Baraba ́si, R. Albert, H. Jeong, Mean-field theory for scale-free random networks, Physica A, Vol. 272, 1999, pp. 173-187.

T. Carletti, S. Righi, Weighted fractal networks, Physica A, Vol. 389, 2010, pp. 2134-2142.

X. Cheng, H. Wang, Q. Quyang, Scale-free network model of node and connection diversity, Physical Review E, Vol. 65, 2000, pp. 4633-4636.

國際替代計量

社群網路對數成長模型

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