社會凝聚機能與社群結構動態對爆紅現象之影響-網絡玻色-愛因斯坦凝聚原理之應用

NCUIR > School of Management at National Central University > Graduate Institute of Business Administration > Electronic Thesis & Dissertation > Item 987654321/48806

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/48806

Title:	社會凝聚機能與社群結構動態對爆紅現象之影響-網絡玻色-愛因斯坦凝聚原理之應用
Authors:	戴廷晃;Ting-huang Tai
Contributors:	企業管理研究所
Keywords:	ABM模型;玻色-愛因斯坦凝聚;社會網絡分析法;爆紅;Agent-Based Model;Bose-Einstein condensation;social network analysis method;Internet Meme
Date:	2011-07-18
Issue Date:	2012-01-05 15:07:23 (UTC+8)
Abstract:	社會科學令人訝異的與自然科學有許多相似的特性，例如冪次法則，在自然科學界與社會科學界都有許多現象背後的統計關係服從冪次法則。其他社會現象例如政府組織、金融市場、經濟自我組織機制等等都可能是自我組織而成的結構，遵循著未知的自然法則，因此利用自然科學研究所發展出來的模擬或是統計方法來預測社會現象的因果似乎變得越來越可行。Bianconi與Barabasi兩位學者將社會網絡中集線器(Hub)的特徵與物理學中的玻色-愛因斯坦凝聚現象相結合，發展出Bianconi-Barabasi模型，奠定可靠的社會網絡分析方法理論，本研究嘗試將社會中的爆紅現象轉化成網絡架構，並以此為出發點，除了原有的BB模型之外，也加入Guimera等學者提出有關團隊組隊機制的Team Assembly理論，延伸網絡中代理人的行為，建立四種不同的以代理人為基礎的模擬模型(ABM)：典型BB模型、BB-TA模型與具有學習行為的BB-TA D2N、D2D等模型，企圖了解爆紅現象的原貌，藉由模擬以上的ABM模型，操弄各種不同的社會參數，研究觀察爆紅現象背後的機制與過程，來尋找可能發生爆紅的條件與社會情境，研究結果發現，社會氛圍與社會的創作活力可能是影響爆紅現象背後機制的兩大要件，這兩項要件的交互組合形成了不同的社會情境，本研究依照不同的社會情境對企業界提出實務上的建議。 Social science and natural science surprisingly have many similar features such as the power law. Many phenomena in both social science and natural science are common and the statistics behind follow the power law. There are other social phenomena such as government organizations, financial markets, economic self-organization mechanisms, etc., may be made of self-organized structure, followed the unknown laws of nature, using natural science simulation or statistical methods to predict cause and effect of social phenomena seems become more feasible. Bianconi and Barabasi combined Hub characteristics in the social network and Bose - Einstein condensation in physics with the development of the Bianconi-Barabasi model, providing a reliable social network analysis method. In strat of this study, we tried to turn the social phenomena, Internet Meme into the social network sturcture. In addition to the original BB model, this study joined the Team Assembly theory, extending the agents’ behavior in the network, establishing four different types of agent-based model (ABM): BB model, BB-TA model and BB-TA D2N, D2D models with learning behavior. This study simulated over the ABM models and manipulated a variety of social parameters in an attempt to understand the mechanisms and processes behind the Internet Meme to find the possible social conditions and social contexets. The results found that the social atmosphere and the creative vitality of society may affect the mechanisms behind the phenomenon of Internet Meme. The interaction of these two elements forms different social contexts. We make practical recommendations to business according to the study of different social context.
Appears in Collections:	[Graduate Institute of Business Administration] Electronic Thesis & Dissertation

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