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  • 學位論文

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

Explore the Background and Social Behavior of the Members of the Internet Community : a Case Study of iThelp.

指導教授 : 沈俊毅

摘要


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。 網路社群伴隨網路發展而蓬勃興起,建構一個無疆界的國度。不同專業知識領域的網路社群其社群成員背景分布不同,對於社群行為的表現也有不同程度的影響。對前述不同知識領域網路社群如能有系統性研究,對於知識社群網站的發展、建置與運用,必能有更大助益。倘能結合學習社群或是與遠距教學、補充教學等相結合,對社會學習與縮短城鄉資源差距或有助益。 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: 一、專業知識網路社群成員背景分布與一般綜合性社群分布明顯不同,專業知識領域與加入社群形式對分布有影響。 二、知識網路社群呈現高度社群行為認同,但個人不同背景變項對社群行為仍有程度不一之顯著差異。 三、參與動機明顯與社群行為表現相關,站方與朋友邀請參加者在社群行為各構面上均呈現高度認同。 根據研究結果做成結論,並對知識網路社群未來發展與研究,在實務方向與學術方向提出建議,以供參考。

並列摘要


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.

參考文獻


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