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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/93733

    Title: 探討網路社群成員背景與社群行為之相關研究 : 以iT邦幫忙為例
    Other Titles: Explore the background and social behavior of the members of the internet community : a case study of iThelp
    Authors: 陳銘嵩;Chen, Ming-Sung
    Contributors: 淡江大學教育科技學系碩士在職專班
    沈俊毅;Shen, Chun-Yi
    Keywords: 網路社群;社群行為;社群成員背景;知識分享;Members of the Internet Community;Social Behavior;Members' Backgrounds;knowledge sharing
    Date: 2013
    Issue Date: 2014-01-23 13:27:42 (UTC+8)
    Abstract: 科技與網路持續的發展,造成社會生活結構上的改變。從而對人類的生活形態與人際關係、資訊與知識的分享及學習形式一直產生影響與變化,不論是身邊的食、衣、住、行、娛樂及資訊傳播與知識學習甚至是文化資產書籍紛紛數位化與資訊化更加重了網際網路的重要性與關鍵性。
    本研究針對知識網路社群iT邦幫忙社群成員個人背景現況與社群行為表現的影響進行調查,研究以問卷調查法進行資料蒐集(N=302),所得資料除進行敘述性統計作為外,以t 檢定、單因子變異數分析(One-Way ANOVA)進行數據分析。研究獲得結論有以下三點:
    The development of technology and internet leads to a shift in the structure of social life, as well as influences and changes the lifestyle, relationships, information and knowledge sharing and forms of learning. Internet plays an important and critical role in our daily life as everything is digitalized. This includes food, clothing, accommodation, transportation, entertainment, information and communication, knowledge learning, books and cultural resources.
    Along with the development of the Internet is the burgeoning internet communities that have no borders. Internet communities with different expertise have different members who have different backgrounds and therefore differ in their social behaviors. Research into the difference in the social behaviors between different internet communities can benefit the development, deployment and applications of these communities. The integration of internet communities into distance learning and supplementary teaching can also enhance social learning and narrow the gap between urban and rural areas.
    The study used iThelp as a case study to explore the background and social behavior of the members of the internet community. Questionnaires were employed (N=302) to collect the data. Descriptive analysis, T-test and One-Way ANOVA were adopted to analyze the results. The conclusions are:
    There is a difference in the distribution of members’ backgrounds between expert internet community and general internet community ; areas of expertise and reasons for joining internet community have an impact on the distribution of members’ backgrounds.
    Expert internet community shows a high level of social behavior recognition while there is a significant difference in the social behavior between members with different backgrounds.
    There is an association between motivation and social behaviors. Website management teams and members who are invited by friends to join internet community show a high level of social behavior recognition.
    The results can enhance the understanding on the social behaviors of internet community and thus provide useful information for teachers and website management teams in the future.
    Appears in Collections:[教育科技學系暨研究所] 學位論文

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