| Summary: | 碩士 === 中原大學 === 企業管理研究所 === 105 === With the prevalence of Mobile Games, numerous of game developers and players are growing significantly. Many players are willing to discuss experiences and suggestions at the forum and thus the online reviews from users become an important source of marketing and game development information. In fact, the discussions from the users are the most direct and real-time information for the developer, but it is rarely sorted out and effectively used. In the past, many enterprises or studies collect the use of consumers from questionnaire, but the answer is limited by the framework. The application of Text Mining can overcome the disadvantage of questionnaire by collecting information from open online review without the limitation of time, space and number of samples. Therefore, in this study, we apply Text Mining to analyze online review of mobile game Pokémon Go from PTT and utilize the web crawler software written in Python to collect the data. We also go through the process of preprocessing, tokenizing, deleting stop word, creating word cloud, dictionary and LDA Topic Model and further to explain and evaluate the analysis results. We categorize the terms of subject and calculate the corresponding appearing frequency of key words and then draw the trend graph to understand the popularity of these key words. Finally, according to the analysis of online reviews, we provide an important basis of marketing strategy for game developers.
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