| DC 欄位 |
值 |
語言 |
| DC.contributor | 企業管理學系 | zh_TW |
| DC.creator | 王顗銘 | zh_TW |
| DC.creator | Yi-ming Wang | en_US |
| dc.date.accessioned | 2015-7-25T07:39:07Z | |
| dc.date.available | 2015-7-25T07:39:07Z | |
| dc.date.issued | 2015 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=102421063 | |
| dc.contributor.department | 企業管理學系 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 本研究透過Bianconi與Barabási兩位學者提出的理論基礎，以物理學上玻色-愛因斯坦凝聚現象奠定可靠的社會網絡分析方法，以及戴廷晃與李偉萍研究中的BB模型將社會中的爆紅現象轉化成網絡架構，並以此為立基點探討產生爆紅現象後的社會狀態，由Rupert與Cetinkaya的研究對於社會網絡產生的熵值與鄰近中心度的觀點代表真實社會中一群對於某項作品擁有共同偏好的成員，對應至真實社會中共同偏好的成員可以再分為粉絲團與後援會兩種形式，以不同形式為基礎藉由網絡模型之鄰近中心度與溫度間的MMF函數關係，使該網絡架構能依循MMF函數關係進行世代演化。透過模型的適應性演化企圖了解不同的粉絲組成形式對於爆紅現象以及產生爆紅後的社會狀態，並且調控整體BB適應演化模型的各項參數觀察模型演化的結果並對應至現實社會，本研究以K-pop為主要分析的對象並與模型演化的結果相呼應。在本研究結果中發現產生爆紅現象後的社會不一定能穩定持續創造潮流，在不同參數下的控制皆會有不同的效果，並且以粉絲團形式的社會網絡進行適應性演化較容易產生爆紅且能在爆紅後進入穩定態。 | zh_TW |
| dc.description.abstract | The main basis of this research is to analysis social states after the Internet Meme, based on the theory of Bose-Einstein Condensation which propound by Bianconi and Barabási. To construct a reliable social network analysis system, this study uses BB model through the study of Tin-Huang Dai and Wei-Ping Li. Entropy and closeness centrality of the social network represent a group of people which has a common preference in real world. To make this study close to the real society, we differentiate two kinds of people which have common preference, fandom and fan club. On the basis of two kinds of fans, BB model conducts adaptive evolution through MMF functions of temperature and closeness centrality in the network model. This study attempts observing the states after the Internet Meme though two different kinds of fans and regulating all the parameter of MMF functions to correspond to the real society environment, K-pop is the main case in the study and to find out why it can create a big wave of music industry in ten years. The results found that the states of a social network may not be a steady state after Internet Meme; adaptive evolution of the social network with fandom more easily achieves Internet Meme and steady state. | en_US |
| DC.subject | 爆紅 | zh_TW |
| DC.subject | 玻色-愛因斯坦凝聚 | zh_TW |
| DC.subject | 鄰近中心度 | zh_TW |
| DC.subject | MMF | zh_TW |
| DC.subject | Internet Meme | en_US |
| DC.subject | Bose-Einstein condensation | en_US |
| DC.subject | closeness centrality | en_US |
| DC.subject | MMF function | en_US |
| DC.title | 社會爆紅現象之動態模擬分析-以K-POP為例之探索性研究 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |