A vector space model approach to social relation extraction from text corpus

Social network analysis (SNA) is significantly about research of social relations as well as structure in social environment. All the dependencies between people, organizations and environment constitute one or several networks. The author presented a vector space model (VSM) approach to extract and represent relations from text corpus. The approach employed VSM to represent the weight value of every social object´s frequency in every text. It reflected the relationships between social objects and text corpus. Then the vector space is decomposed into a new vector space reflecting the relationships between social objects. It is concluded that the application of VSM can obtain deeper social relations hid in text and text corpus and increase the effect and efficiency of social network analysis of text corpus.