Using Online Community to Predict User's Preference: A Combination of Facebook and Cloud Computing

• Main Authors: Yuan-Jhen Chen, 陳源鎮
• Other Authors: Jung-Lung Hsu
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/61595881594318428403

碩士 === 開南大學 === 資訊管理學系 === 101 === Facebook is well known social networking site that offers many functions. So the user can freely share ideas and status. Traditional WOM mainly through spoken language, so difficult to preserve. However, online WOM existence in the network, so the impact is greater than the traditional WOM. Many previous studies have impact for online WOM comments from business website analysis, but few studies using online community to predict user's preference, as a basis for inference online WOM. Therefore, this research goal attempt to propose a feasible framework, which to demonstrate how to combine Google App Engine cloud development environment with Facebook. And used to collection information on the status of the user, in order to evaluate the user's preferences. This study proposes a framework mainly through Facebook Graph API is stored in the data collection out of the cloud database for analysis. Finally the use of traditional validated questionnaire compared with the experimental results. The results from the analysis of the frequency content of user state data shows that the more active types of user behavior with a reputation for passing information dissemination has some effect, but the system some functions need to be strengthened. Suggestions for future research is application of Internet marketing which can refer to this framework, the development of appropriate environment to compile Facebook user data. If combined with location-based cloud services, which may help companies achieve timely identify the user side, providing for appropriate recommended product, thus improving product satisfaction positive online WOM purposes.