Extracting Social Network among Various Entities from Chinese News Stories by Content Analysis

Social networks have recently attracted much attention for their importance to the semantic Web. Several methods exist to extract social networks for people from the Web based on co-occurrence information. This paper proposed a content analysis based method for automatic obtaining social networks among various entities from Chinese event-based news stories. First, the input articles are annotated by lexical analysis. Second, the relationships among all entities are extracted by the way of main verbs recognition. For directed graph expression, an arrow is drawn between each pair of entities which have relationship from the agent argument to the patient one. Finally, all relationship expressions were established to build the social network up. Experiment results for relationships extraction made on 50 independent news articles indicate that our method can work well.