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研究生: 魏浩翔
Wei, Hao Xiang
論文名稱: 分享脈絡:社群媒體訊息散播行為視覺化
ShareFlow: Information Diffusion Visualization with Social Media
指導教授: 紀明德
Chi, Ming Te
學位類別: 碩士
Master
系所名稱: 理學院 - 資訊科學系
論文出版年: 2015
畢業學年度: 104
語文別: 中文
論文頁數: 61
中文關鍵詞: 資訊視覺化資訊擴散社群媒體
外文關鍵詞: Data visualization, Information diffusion, Social media
相關次數: 點閱:84下載:38
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  • 本篇論文針對社群使用者在社群網路文章上的互動行為進行研究,以視覺化工具Shareflow探索互動過程中造成資訊擴散的意見領袖以及傳播路徑。本研究主要分成兩個部分,第一部分為單一篇文章的分享路徑視覺化,基於階層化邊線綑綁(Hierarchical edge bundles)方法,根據控制點的引導將鄰近邊線進行綑綁,透過邊線捆綁舒緩資料量過大時造成之視覺混亂(visual clutter)問題。第二部分為粉絲專頁文章視覺化,分析多篇文章中具有多次分享、留言行為之使用者,呈現整體社群中積極活動的使用者以及其相關文章的視覺化。最後提供即時互動操作介面,以並列方式呈現出資料的廣度和深度,本研究的貢獻為提供一套視覺化工具,協助使用者探索臉書社群網路中的資訊散播過程以及發掘積極活動的臉書使用者。


    In this thesis, we propose a visualization tool, “Shareflow”, for observing the user activities in social media posts, and to explore opinion leaders and the propagation path caused by the information diffusion. Our approach contains two parts. The first part is a visualization of propagation path for a post in Facebook fanpage. Based on hierarchical edge bundles, we optimize the layout to reduce visual clutter caused by excessive information. The second part is visualization for a summary of posts in Facebook fanpage. It provides a tool for analysis the active users through their sharing and comments activities; In addition, we provide a real-time interactive interface, which demonstrates the breadth and depth of information concurrently.

    摘要 i
    Abstract ii
    目錄 iii
    圖目錄 v
    第一章 緒論 1
    1.1 研究動機與目的 1
    1.2 問題描述 2
    1.3 論文貢獻 3
    1.4 論文章節架構 3
    第二章 相關研究 4
    2.1 社群網路視覺化 4
    2.2 圖形簡化 8
    2.3 邊線捆綁 10
    第三章 研究方法與步驟 13
    3.1 系統架構 13
    3.2 資料撈取、整合與分析 14
    3.2.1 資料撈取 15
    3.2.2 資料整合與分析 16
    3.3 階層化邊線捆綁 18
    3.4 單一篇文章分享路徑視覺化 20
    3.5 粉絲專頁視覺化 25
    3.6 互動機制 31
    第四章 實驗結果與討論 35
    4.1 實作與實驗環境 35
    4.2 個案研究 35
    4.2.1 單一粉絲專頁觀察(以懶人時報為例) 36
    4.2.2 單一事件觀察(以2015年11月巴黎襲擊事件為例) 38
    4.3 使用者測試(初測) 44
    4.4 使用者測試(線上問卷) 49
    4.5 限制 55
    第五章 結論與未來工作 58
    5.1 結論 58
    5.2 未來工作 59
    參考文獻 60

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    [15] https://developers.facebook.com/docs/graph-api/advanced/rate-limiting

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