• DocumentCode
    2093401
  • Title

    Sentiment in Science - A Case Study of CBMS Contributions in Years 2003 to 2007

  • Author

    Verlic, Mateja ; Stiglic, Gregor ; Kocbek, Simon ; Kokol, Peter

  • Author_Institution
    Fac. of Electr. Eng. & Comput. Sci., Univ. of Maribor, Maribor
  • fYear
    2008
  • fDate
    17-19 June 2008
  • Firstpage
    138
  • Lastpage
    143
  • Abstract
    This paper presents an overview of past papers published at the CBMS symposiums from a content analysis point of view. A simple, yet effective word counting using Harvard Psycho-Social dictionary was used to estimate different aspects of sentiment that can be present even in scientific papers. Using simple statistics we uncover some of the very interesting trends in the last five CBMS symposiums. Additional to pure statistics we used some of the most advanced classification techniques to see if there are any significant differences in psycho-social texture of the accepted papers. It was also shown that building machine learning models on this kind of data can result in some very interesting generalizations of the underlying data.
  • Keywords
    learning (artificial intelligence); psychology; Harvard Psycho-Social dictionary; content analysis; machine learning models; sentiment; Bioinformatics; Biomedical imaging; Computer science; Data mining; Dictionaries; Humans; Machine learning; Psychology; Speech; Statistics; machine learning; sentiment analysis; text mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer-Based Medical Systems, 2008. CBMS '08. 21st IEEE International Symposium on
  • Conference_Location
    Jyvaskyla
  • ISSN
    1063-7125
  • Print_ISBN
    978-0-7695-3165-6
  • Type

    conf

  • DOI
    10.1109/CBMS.2008.135
  • Filename
    4561971