A Conceptual Framework of E-Commerce Supervision System Based on Opinion Mining

The Internet significantly reshapes traditional commerce mode, making online business ubiquitous and indispensable. Others´ opinions are influential when we make a decision, which is complicated by tremendous and misleading information. According to opinion mining techniques, we propose a novel conceptual framework which is designed to exploit the potentials of opinion mining in e-commerce domain. Based on the various text corpora we crawled from targeted internet source, we utilize the sentiment analysis principle and algorithm to provide convenient and assistant services, such as opinion spam detection, opinion search and retrieval, opinion summary, opinion question answering and opinion recommendation, to e-commerce participants such as potential customers, manufacturers, third-party traders or retailers, and regulators. Besides, the system introduces a novel NLP toolkits excelling in handling the Chinese corpora than most of previous alike work. The system is especially helpful to regulators by providing useful applications which can be utilized to make administrating decisions.