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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/120256


    Title: 應用集合視覺化之社群網路使用者交集活動探索與分析工具
    PageSet: Visualization of Social Network User Activity Intersections
    Authors: 廖春閔
    Liao, Chun-Min
    Contributors: 紀明德
    Chi, Ming-Te
    廖春閔
    Liao, Chun-Min
    Keywords: 資料視覺化
    社群網站
    集合資料
    階層資料
    圖標符號
    Date: 2018
    Abstract: 本論文針對兩個階層資料共同含有的元素進行分析的工作任務(Task),參考現代最先進的集合交集視覺化方法,針對視覺化表達資料的集合特別是階層關係,集合與元素的屬性瀏覽強化,應用到分析社群媒體使用者活動資料分析,找出關鍵的使用者和行為。我們以多視圖呈現和互動操作互相串聯達成以下目標,瀏覽粉絲專頁的貼文與使用者資料,比較粉絲專頁間的使用者活動情形,觀察重疊活動使用者的活動情形,查詢粉絲專頁的貼文與使用者資料細節。根據資料的特性,以階層化視覺化方法表現階層化的集合關係,以及專注在發生交集的元素呈現概覽,達成可靠的可擴展性。最後比較目前最先進的集合交集視覺化方法支援的工作任務、可擴展性討論我們系統的優點和限制,最後提出未來能精進的研究方向。
    Analyzing the common elements belong to the two collections of hierarchical data is the critical task of our work. According to the state of the art intersection visualization method, we enhance the visual expression of data, especially for the hierarchical relationship, set/element attribute exploration, and apply our approach on social media to identify key users and behaviors by user activity data analysis. We use multi-view visualization and interaction to achieve the following goals: browse the posts and user profiles of pages(set of posts), compare user activity between pages, observe the activities of the intersection users, and highlight the detail information of posts and user profiles. According to the characteristics of the data, the hierarchical visualization method such as Sunburst and Treemap is used to represent the hierarchical relationship, and focus on presenting the intersection elements only to achieve reliable scalability. Finally, we compare the work tasks and scalability supported by the state of the art set visualization method, discuss the advantages and limitations of our work, and conclude the research direction that can be refined in the future.
    Description: 碩士
    國立政治大學
    資訊科學系
    104753040
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0104753040
    Data Type: thesis
    DOI: 10.6814/THE.NCCU.CS.019.2018.B02
    Appears in Collections:[Department of Computer Science ] Theses

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