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    政大機構典藏 > 傳播學院 > 新聞學系 > 期刊論文 >  Item 140.119/134152


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/134152


    Title: 網路統獨的聲量研究：大數據的分析
    The Study of Internet Politics on Southern Weekly New Year`s Greeting Incident in 2013
    Authors: 劉嘉薇
    Liu, Jia-Wei
    Contributors: 新聞系
    Keywords: 統一 ; 獨立 ; 統獨 ; 大數據 ; 網路 
    Unification ; Independence ; Unification-independence ; Big Data ; Internet
    Date: 2017-03
    Issue Date: 2021-03-02 14:47:18 (UTC+8)
    Abstract: 統獨議題是臺灣最重要的政治分歧，本研究透過7,000多個網路頻道大數據，分析網路上的統獨輿論。因為統獨屬於較敏感的政治性議題，網路的匿名性也有助於探知敏感議題的意見表達。網路民意的大數據分析在國內政治學研究仍屬少見，本文也用了一些篇幅探討它的信效度。本研究發現在統獨聲量的分布中，偏向獨立者高於統一。以「對象」而言，「中國」及「臺灣」被提及次數最多。在聲量來源方面，兩岸議題討論聲量中，高達48%集中在社群網站，其中單一網站聲量最多者為PTT。再進一步考慮到統獨議題的聲量情緒分析，平均每出現6篇正面情緒聲量時，同時會出現10篇負面情緒聲量。以上網路大數據的分析不同於民意調查的結果，網路大數據偏向獨立的聲量較高，維持現狀是民調主要的結果，但在網路的聲量很少，可能與網路具有匿名特質有關，讓網民亦在網上表達意見，值得重視。本研究分析網路大數據，而這與以民意調查進行統獨研究時，研究者想方設法希望挖掘「維持現狀者」骨子裡想法的做法異曲同工。不同於民意調查之處在於，民意調查以個體為分析單位，網路大數據分析以聲量為分析單位，兩者獲致不同結果，兩者都是民意，但當政府和政黨疾呼重視網民意見時，網路大數據呈現異於民調的結果，民調試圖理解「全民」的意見，但實際抽樣時可能缺乏年輕人的意見，網路大數據有助於理解「網民」的意見，兩者皆需做為當局執政依據。尤其當網路論壇或社群媒體民意四起時，更彰顯網路大數據分析的價值。
    The Unification-independence issue is an major political cleavage in Taiwan. This study analyzed the public opinion of unification-independence on the internet through big data. We found that in the distribution of unification-independence sound volume, the number of the independence sound volume was higher than that of unification. In the aspect of the target, ＂China＂ and ＂Taiwan＂ were mentioned the most. In the source of the sound volume, social media was the main source, and PTT is the main channel. Furthermore, the sentiments of sound volume were that there were 6 positive sound volume and 10 negative sound volume at the same time. The above results were not different from the results of the surveys, and it deserves to be taken seriously by the administration. The value of big data analysis is obvious, especially when online forum or social media rise.
    Relation: 政治科學論叢, 71期, 113-166
    Data Type: article
    DOI 連結: https://doi.org/10.6166/TJPS.71(113-166)
    DOI: 10.6166/TJPS.71(113-166)
    Appears in Collections:[新聞學系] 期刊論文

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