A Novel Approach for Clustering Chinese Blogs by Embedded Sentiment Based on Graph Similarity

摘要

Blog clustering is an important approach of web public opinion analysis. In this paper, an integrated graph-based approach for representing and clustering Chinese blogs by embedded sentiment is proposed. Graph-based representation and relevant clustering algorithm are applied. This graph-based blogs representation model considers not only sentiment words but also some structural information. Experimental results show that comparing with applying initial graph-based document representation model and vector space document representation model, the integrated graph-based document representation model has better quality in clustering Chinese blog documents.