研究生: |
翁瑞臨 Weng, Jui-Lin |
---|---|
論文名稱: |
影音分享社群使用者的影音內容貢獻行為之相關因素研究 The Video Content Contribution Factors and Behaviors of Users in an Online Video-Sharing Community |
指導教授: |
邱瓊慧
Chiu, Chiung-Hui |
學位類別: |
碩士 Master |
系所名稱: |
資訊教育研究所 Graduate Institute of Information and Computer Education |
論文出版年: | 2018 |
畢業學年度: | 106 |
語文別: | 中文 |
論文頁數: | 137 |
中文關鍵詞: | 影音分享社群 、影音內容貢獻行為 、社會因素 、個人需求因素 、偏最小平方法 |
英文關鍵詞: | video-sharing community, video content contribution, social factors, personal needs factors, partial least squares |
DOI URL: | http://doi.org/10.6345/THE.NTNU.GICE.012.2018.F02 |
論文種類: | 學術論文 |
相關次數: | 點閱:144 下載:1 |
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本研究旨在探討影音分享社群使用者貢獻原創影音內容的因素與其影音內容貢獻行為之關係。研究對象為2017年5月20日至6月10日此段期間,臺灣地區具有於影音分享社群分享原創影片之經驗的使用者。本研究於LimeSurvey線上問卷系統上建置問卷,首先與研究者生活週遭有連結、有分享原創影片經驗的友人接觸,解釋研究內容並徵得同意後,邀請其作為參與者,再由這些參與者協助研究者和其他具有原創影片分享經驗的人聯繫,在影音分享社群分享線上問卷連結,邀請同樣具有在影音分享社群分享原創影片之經驗者參與問卷調查,最終獲得有效樣本416人。研究所得資料以結構方程模式(Structural Equation Modeling, SEM)來探討影音內容貢獻因素與影音內容貢獻行為之間的關係,本研究利用偏最小平方法(Partial Least Squares, PLS)來分析結構方程模型的信度、效度,以及預測模型解釋力;最後以獨立樣本T檢定與單因子變異數分析分析不同背景變項之下,研究對象的影音內容貢獻因素與影音內容貢獻行為是否有差異。
研究結果表示,社會因素所涵蓋的歸屬感、聲望、互惠、社會影響、社會關係、社會支持等構面對影音內容貢獻行為有良好的解釋力,代表研究對象影音分享社群貢獻原創影音內容的社會因素為預測影音內容貢獻行為的顯著變項,而個人需求因素所涵蓋的學習、樂趣、利他等構面則對影音內容貢獻行為則沒有顯著解釋力;在不同背景變項之下,研究對象影音內容貢獻因素與影音內容貢獻行為的差異結果表示,性別、年齡變項對影音內容貢獻因素與影音內容貢獻行為無顯著差異,而教育程度、每日使用時間、與每週使用頻率等變項對影音內容貢獻因素與影音內容貢獻行為則有顯著差異。
The purpose of this study was to explore the video content contribution factors and behaviors of users in an online video-sharing community. The research participants were online video-sharing communities’ users during the period from 20th May 2017 through 10th June 2017, who had had the experience of sharing original videos in an online video-sharing community. The research method adopted a questionnaire survey on LimeSurvey system to collect data. First, the researcher contacted friends who had experience in sharing original videos, and explained the research content and obtained consent, then invited them as participants. These participants then assisted to contact others who had shared original videos before, and shared the online questionnaire links to respective video-sharing communities. After finishing collecting data, the Structural Equation Modeling (SEM) was used to explore the relationship between the video content contribution factors and behaviors. The study adopted Partial Least Squares (PLS) to analyze reliability, validity, the predictive force of the model. This study also used independent-sample T-test and One-way ANOVA to understand differences between factors and the behavior based on different subjects’ background variables.
The result of PLS showed that social factors, including sense of belonging, reputation, reciprocity, social influence, social tie and social support, had a positive correlation on the video content contribution behavior. However, personal needs factors, including learning, enjoyment, and altruism were not correlated. It predicted participants’ social factors would positively affect video content contribution behavior. The results of independent-sample T-test and One-way ANOVA showed that there was no significant differences between gender and age variables on the video content contribution factors and behaviors. However, background variables, including education, hours per day of using video-sharing community, and frequencies per week of using video-sharing community had significant differences.
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