• DocumentCode
    257475
  • Title

    An opinion detection algorithm based on online posts´ relation

  • Author

    Sun Zhi ; Peng Qinke

  • Author_Institution
    Syst. Eng. Inst., Xi´an Jiaotong Univ., Xi´an, China
  • fYear
    2014
  • fDate
    4-6 June 2014
  • Firstpage
    153
  • Lastpage
    156
  • Abstract
    In recent years, opinion detection in posts has attracted more attentions, which can help us to understand people´s reaction to the events effectively. In opinion detection, the representation of the posts´ relations is important. Most of the existing researches utilized the vector space model and some similarity computing methods to describe the relations of the posts. But they ignored that the posts´ relations are complex containing both the semantic part and the content part. In this paper, we first proposed a new hybrid post relations combining semantic similarity and content relation. Then we detected the opinions of online news posts with the networks of the hybrid posts´ relations. The results show that our methods have better performance.
  • Keywords
    natural language processing; vectors; content part; content relation; hybrid post relations; online news posts; online post relation; opinion detection algorithm; post relation representation; semantic part; similarity computing methods; vector space model; Accuracy; Communities; Computers; Internet; Semantics; Support vector machines; Vectors; news posts; opinion detection; posts´ relation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Information Science (ICIS), 2014 IEEE/ACIS 13th International Conference on
  • Conference_Location
    Taiyuan
  • Type

    conf

  • DOI
    10.1109/ICIS.2014.6912124
  • Filename
    6912124