e-Learning, e-Education, and Online Training. 4th International Conference, eLEOT 2018, Shanghai, China, April 5–7, 2018, Proceedings

Research Article

Research on Data Mining Technology of Social Network Associated Information

  • @INPROCEEDINGS{10.1007/978-3-319-93719-9_3,
        author={Yanxin Jiang and Xian Mei and Guanglu Sun},
        title={Research on Data Mining Technology of Social Network Associated Information},
        proceedings={e-Learning, e-Education, and Online Training. 4th International Conference, eLEOT 2018, Shanghai, China, April 5--7, 2018, Proceedings},
        proceedings_a={ELEOT},
        year={2018},
        month={7},
        keywords={Social network Data mining Ideological Political education},
        doi={10.1007/978-3-319-93719-9_3}
    }
    
  • Yanxin Jiang
    Xian Mei
    Guanglu Sun
    Year: 2018
    Research on Data Mining Technology of Social Network Associated Information
    ELEOT
    Springer
    DOI: 10.1007/978-3-319-93719-9_3
Yanxin Jiang1,*, Xian Mei2, Guanglu Sun2
  • 1: Heilongjiang University
  • 2: Harbin University of Science and Technology
*Contact email: jyx1977@sohu.com

Abstract

With the popularization of Internet social networking service, the results of association data mining between friend dynamic, microblog and moments that user posting and giving feedback information, which have important influence on government planning, business management and personal affairs decision-making activities. This paper studies the data mining technology of social network related information, analyzes the text data in social network by using the finite state automata (DFSA) and word frequency - reverse file frequency (TF-IDF), and using tree algorithm to sort the data. The simulation results show that this method can realize the classification data mining of social network related information.