淡江大學機構典藏:Item 987654321/87735
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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/87735


    Title: 社群網路資訊傳播效果之量化研究 : 以臉書為例
    Other Titles: Quantitative measures on the spread of information in social networks : Facebook as an example
    Authors: 李家宏;Li, Chia-Hong
    Contributors: 淡江大學資訊管理學系碩士班
    鄭啟斌;Cheng, Chi-Bin
    Keywords: 社群網路;資訊傳播;口碑行銷;Spread of information;Word-of-Mouth Marketing;Social Network
    Date: 2013
    Issue Date: 2013-04-13 11:37:23 (UTC+8)
    Abstract: 社群網路的崛起，除了可以讓使用在網路上交換想法與意見，其快速傳播資訊的能力也可以達到良好的口碑行銷效果，但如何善用社群網路本身的架構以提升口碑行銷的效率卻尚未有詳細的研究。本研究的目的在探討社群網路中節點的群聚特性是否影響資訊傳播的效率。本研究以最受歡迎的社群網路臉書為對象，量化分析節點的群聚中心性對於傳播效率的影響程度。由於實際的網路太大難以分析，我們以抽樣的方式由實際的社群網路中抽取並形成一個四萬個節點的網路，然後以電腦模擬的方式模擬資訊傳播的過程。本研究使用Pajek網路分析軟體來衡量各節點的中心性，並分別以不同中心性的節點做為初始節點進行資訊傳播模擬，以驗證節點的群聚中心性對於資訊傳播效率的影響。
    The advent of social networks not only enable the exchanges of ideas but also facilitate the use of word-of-mouth (WOM) marketing due to its capability of fast broadcasting of information. However, how to take the advantage of the network structure to enhance the efficiency of WOM is not well studied. The purpose of this study is to investigate the effect of the centrality of a node in the network on the efficiency of information broadcast of the network. This study uses the most popular social network, Facebook, as an example to analyze the broadcasting efficiency of nodes in terms of their centralities. Since the real network is too huge to be analyzed, a sample network with 40000 nodes is randomly abstracted from the Facebook social network. Information broadcasting process of the sample network is observed through computer simulation. The software Pajek is employed to measure the centralities of nodes, and then nodes with different degrees of centrality are chosen as initial nodes in a series of experiments of information broadcast to evaluate the effect of node centrality on the efficiency of information broadcast of the network.
    Appears in Collections:[Graduate Institute & Department of Information Management] Thesis

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