Abstract
The Opinion Detection from blogs has always been a challenge for researchers. One of the challenges faced is to find such documents that specifically contain opinion on users’ information need. This requires text processing on sentence level rather than on document level. In this paper, we have proposed an opinion detection approach. The proposed approach focuses on above problem by processing documents on sentence level using different semantic similarity relations of WordNet between sentence words and list of weighted query words expanded through encyclopedia Wikipedia. According to initial results, our approach performs well with MAP of 0.28 and P@10 of 0.64 with improvement of 27% over baseline results. TREC Blog 2006 data is used as test data collection.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Esuli, A., Sebastiani, F.: SentiWordNet: A publicly available lexical resource for opinion mining. In: Proceedings of LREC 2006, 5th Conference on Language Resources and Evaluation, Genova (2006)
Zhou, L., Twitchell, D.P., Qin, T., Burgoon, J.K., Nunamaker, J.F.: An exploratory study in deception detection in text-based computer mediated communication. In: Proceedings of the 36th Hawaii International Conference on System Sciences, HICSS 2003 (2003)
Ounis, I., Rijke, M., Macdonald, C., Mishne, G., Soboroff, I.: Overview of the TREC 2006 Blog Track (2006)
Macdonald, C., Ounis, I., Soboroff, I.: Overview of the TREC-2007 Blog Track (2007)
Pederson, T., Patwardhan, S., Michelizzi, J.: WordNet:: Similarity- Measuring the relatedness of concepts
Ounis, I., Lioma, C., Macdonald, C., Plachouras, V.: Research Directions in Terrier: a Search Engine for Advanced Retrieval on the Web. Novatica/UPGRADE Special Issue on Next Generation Web Search 8(1), 49–56 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Missen, M.M.S., Boughanem, M. (2009). Using WordNet’s Semantic Relations for Opinion Detection in Blogs. In: Boughanem, M., Berrut, C., Mothe, J., Soule-Dupuy, C. (eds) Advances in Information Retrieval. ECIR 2009. Lecture Notes in Computer Science, vol 5478. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00958-7_75
Download citation
DOI: https://doi.org/10.1007/978-3-642-00958-7_75
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-00957-0
Online ISBN: 978-3-642-00958-7
eBook Packages: Computer ScienceComputer Science (R0)