| Summary: | 碩士 === 國立虎尾科技大學 === 資訊管理系碩士班 === 105 === In this modern age where information explosion takes action in every minute, Big Data has raised a lot of eyebrows, becoming one of the hottest issue recently. This has to be credited to its wide coming sources, for instance, governmental open source, social media websites, Bulletin Board System (BBS), etc. These platforms share one common character, which involves various users delivering messages through these platforms, establishing a gigantic social community database. Furthermore, these data are able to be used in diversified theme analysis.
However, since the olden days if one attempted to practice data analysis via users’ opinion collection, it relies on market research manually. The upshot is that not only time consuming, but the number of samples are usually insufficient, leading to a consequent that below expectation. In addition, if the collection takes too much time, but unable to match the requirement form the client, there is a risk that missing the opportunity of the market. Therefore, the question of how to present crucial information from a massive social community database, has currently turn into a significant subject.
In this research, the researcher took Jorsindo Motor Club as an example, by created a recommendation system of bike safety equipment, with the assist of its database, and then captured articles form the forum, instituting structured data. After pre-processed these data, the researcher had extracted the information by text mining. In this procedure, data captured and words dismantled had been practiced in every subjects and replies. Besides, key-words had been analyzed, and a library of word meaning had been organized as the base of data analysis, including positive and negative side. The next step was the operation of semantic analysis, this was used for discussing the positive or negative emotion of users form the forum’s subjects and replies, with the help of word meaning library. Besides, users were able to personalize vocabularies, improving the accuracy of emotional analysis. This system is not only providing the tendency of user’s contents, but beneficial for analyzing information for reference in decision.
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