近年來，「社群媒體」與「共享經濟」結合的行動電商發展，方興未艾，其中以UBER進軍各國計程車市場所引起的風潮為較知名的案例。目前UBER 在臺灣營運是否合法的爭議漸增，尤其涉及叫車方式、彈性費率、司機乘客互評、稅制等課題，皆面臨適法性之挑戰，因此，若能經由社群媒體對於UBER相關課題之網路文本進行意見挖掘，進而了解民眾對UBER適法性的情感態度，則可提供臺灣相關單位推動類似UBER化計程車服務的參考。本研究使用爬蟲系統蒐集UBER 網路意見文本，進行意見挖掘並建構三元決策情感分析模式。該模式係將情感傾向區分為正面情感、中立情感與負面情感。實證結果顯示，討論聲量前三名的營運話題分別為營運制度、取締與抗議以及稅務與收費。民眾對於UBER 在臺營運之網路平台服務的評價，整體情感趨勢係以正面偏中立為主，高於負面情感傾向。整體負面情感趨勢則為UBER營運合法性之爭議，討論量以非法營業與未盡繳稅義務最多。因此，UBER須先取得合法執業許可及繳稅，方可在臺營運。
Mobile commerce business combining sharing economy and social media are now in the ascendant, especially UBER launches into taxi markets worldwide which becomes the most attractive case study in research literatures. Nowadays, issues of legal operations concerning service calling, flexible fares, rating system between drivers and passengers and tax are still in dispute for UBER in Taiwan. It will be very helpful for Taiwan’s authorities and taxi operators if users can understand and accept similar services like UBER by using social media mining and sentiment analysis.Crawler systems were used to collect text data in social media and public opinion mining and sentiment analysis were sequentially performed in this study. A model based on the theory of three-way decisions was used for sentiment analysis which included 3 sentiment zones: positive, negative and neutral. Results of the empirical study showed that the three topics about UBER operations concerning operation mechanism, regulation and protest and taxation problems were discussed extensively in Taiwan. The hottest topic was Internet platform services offered by UBER which won positive and neutral orientation tendency more than negative one significantly. The whole negative orientation tendency focused on dispute of UBER’s illegal operations in Taiwan. It is evident that the first priority for UBER is to apply legal permission and pay tax arrears as soon as possible if UBER attempts to continue operations in Taiwan.