Predictive Market Trend Analytics for Innovative Products: Driverless Car Case Study

• Main Authors: Anghan Li, 李昂翰
• Other Authors: Chuan-Jun Su
• Format: Others
• Language: en_US
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/23848010122760752723

碩士 === 元智大學 === 工業工程與管理學系 === 104 === In these few years, because of the high amount of companies and products that keep increasing, the understanding of the market trend has become an important issue for companies to survive in the competitive environment. Fortunately, with the development of internet, people are used to share every single thing on the popular social media platform such as Twitter, and we can know their opinion and deduce the market trend by analyzing these data. In this research, we propose a framework called Product Improvement Framework based on Social Media Analysis (PIF-SMA) to extract the data from the popular social media platform and make it useful by using word2vec which is created by Google. Considering that the data extracted from the social network contains mess information, we make the system smarter by processing the data using ontology. Due to the nature of the data we extracted from social network is huge, the framework is built on the Hadoop and Spark platform which is the most popular cluster system platform in the big data field to make the PIF-SMA framework work in higher efficiency even close to real time processing. By analyzing social media, the PIF-SMA framework proposes to provide an easy way for company not only to understand the future of market trend but also to know the functions which customers will care about in the product.