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
Link To Document