According to the study “Year 2010 Key Political Issues Discussed by Public and Consensus Online - Case Study: Capital Punishments”, Internet mining (via extracting from recursive bubbles and analysis of blogs and Plurk) yields conclusions similar with those drawn from polls and surveys. In addition to the analysis of texts on blogs and Plurk, this paper aims to construct a research structure for the positive and negative connotations. The texts for online public opinions refer to the blogs or microblogs posted online. However, not all the issues can arouse stark contrasts of opinions like in the case of death penalty. Therefore, this paper intends to extend the recursive bubble method used in Internet mining by developing analytical models for positive and negative connotations, in order to expand the analytical scope of public opinions. Meanwhile, a trend analysis is performed to keep track of changes in public stance. A list of key words is made to incorporate all the key words used to commenting government policies, so as to facilitate the determination of the positive and negative opinions in the texts with IT systems. The focus of this research project is to develop crowdsourcing mechanisms able to determine positive and negative connotations with the collaborative concept of Web 2.0. A collaborative operating system is put into place to segment the mechanism of determining positive and negative connotations into sub-questions and tasks. Internet users and bloggers are then called upon to process the engineering of the positive and negative connotation reading. Conclusions are drawn with systematic statistics. To sum up, the purposes of this innovative research project are as follows: (1) the integration with electronic governance studies and the evaluation of the feasible scope for Internet tools in practice; (2) the analysis of public opinions on government policies expressed in blogs and microblogs in order to construct a new analytical pattern for topical issues and quickly identify the public responses; (3) the development of a response mechanism to detect and determine the stance of public opinions on a real-time basis.
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