Opinion detection research relies on labeled documents for training data, either by assumptions based on the document's origin or by using human assessors to categorise the documents. In recent years, blogs have become a source for opinion identification research (TREC Blog06). This study analyses the part-of-speech proportion and the words used within various corpora, determining key differences and similarities useful when preparing for opinion identification research. The resulting comparisons between the characteristics of the various corpora is detailed and discussed. In particular, opinion-bearing and non-opinion Blog06 documents were found to display a high level of similarity, indicating that blog documents assessed at the document level cannot be used as training data in opinion identification research.
|Cite as: Osman, D., Yearwood, J. and Vamplew, P. (2007). Using Corpus Analysis to Inform Research into Opinion Detection in Blogs. In Proc. Sixth Australasian Data Mining Conference (AusDM 2007), Gold Coast, Australia. CRPIT, 70. Christen, P., Kennedy, P. J., Li, J., Kolyshkina, I. and Williams, G. J., Eds. ACS. 65-75. |