With the rapid development of social network, people can present or share their opinions and emotions on the micro-blog, and as a result, large amount of blog texts and emotional information of different topics are produced. As the traditional text mining algorithms cannot deal with these blog texts with fractional contents and different personal emotions effectively, this paper presents a novel weighting computation approach based on the key characters of micro-blog posts to get the dynamic interests of bloggers on different times. Furthermore, based on the emotion classification, the emotion transition tendency analysis can also be implemented. Experimental results show the feasibility of the presented approach.