Online Public Opinion Systems (OPOS) target at collecting, analyzing, summarizing and monitoring massive public opinions on the Internet in real time. Meanwhile, OPOS often have the ability to identify the key or sudden events, and thus notify related people immediately for rapid responses to these events. As part of this endeavor, this paper introduces the architecture and techniques of an OPOS that has been used by several large enterprises. This self-designed OPOS generally contains data layer, computation layer and application layer from bottom to up. We first introduce the basic function and key techniques of each layer, and then present several typical yet important algorithms on the computation layer. Experimental results on real-world data validate the effectiveness of algorithms fixed in our system. Last but not the least, a system demonstration in a ship-building company is provided to justify the value of our OPOS for real enterprises.
['Lu Zhang', 'Xiaopeng Wang', 'Zhan Bu', 'Jie Cao', 'Zhiang Wu']
Online Public Opinion System: Design and Applications