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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/115078


    Title: 社群媒體傳散資訊能力之研究-以臉書分享為例
    Authors: 劉慧雯;徐國偉;紀明德
    Contributors: 傳播學院
    Keywords: 社群媒體;臉書;資訊工具
    social media;Facebook;information system
    Date: 2013
    Issue Date: 2017-12-08 14:50:00 (UTC+8)
    Abstract: 自臉書在台灣社會風行以來，一直都是主流媒體之外，最重要的社交平台 之一，提供了任何一位有意願的閱聽人一種「能夠採取行動」的機緣(affordances)。 現在的問題是，人與科技互動的「結果」能否被評估？本研究希望借用資訊系 統工具，蒐集並處理經驗資料，以瞭解臉書上資訊傳遞的路徑、規模，與傳散 型態。 本研究設定以網路原生媒體、人、事資訊被分享傳遞的情況，以及其他使 用者轉貼等兩種資訊傳遞活動為觀察對象，試圖建立這些公開資訊所記錄的資 訊傳遞頻率、型態與模式。 而為了使這些工作可以脫離人為登錄在人力、時間、精力以及出錯率方面 的限制，本研究將與資訊科技專長研究人員合作，一方面建構關於社群媒體效 益評估的可能模式，另一方面則開發合適於抓取蒐集、分析、表達這些材料的 資訊系統工具。 本研究是以將與資訊科學專長的研究者合作，一方面在人文向度上設定研 究議題，一方面則借重資訊系統工具的效率，透過開發抓取、登錄、分析資料 的系統工具，完成對大筆臉書資料的考察。
    Facebook has offered the affordances to audiences whoever willing to 'take actions' since it earned the popularity in Taiwan. It has become one of the most important social media outside the mainstream media. The question is, is it possible to evaluate the 'consequences' of interactions between human beings and technology? To uncover the paths, scale, and the dispersion types of information, this research attempts to apply the information system tools to collect and process the empirical data. The main targets of this study include two types of information transfer: first is how the internet-origin information, people, events on social media are shared and forwarded; second is the re-post by other users. This is to clarify the frequency, and type of how the public information are dispersed. To avoid the limitations from manual coding, such as working hours and typing errors, the research will work with information technology experts to establish the evaluation methods for social media effects and develop new methods that fulfill the demand for data collection, analysis and presentation. With support from information scientists, this research focuses on two dimensions. Firstly, the research questions are set in human dimension. And secondly, this research utilizes the efficiency of information system to develop tools for data retrieval, coding, and analysis to complete the observation of big data piles from Facebook.
    Relation: 執行起迄：102.08-105.07
    計畫編號: NSC102-2420-H004-045-MY3
    Data Type: report
    Appears in Collections:[新聞學系] 國科會研究計畫

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