Craig Macdonald
ABSTRACT
In opinion-finding, the retrieval system is tasked with retrieving not just relevant documents, but which also express an opinion towards the query target entity. Most opinion-finding systems are based on a two-stage approach, where initially the system aims to retrieve relevant documents, which are then re-ranked according to the extent to which they are detected to be of an opinionated nature. In this work, we investigate how the underlying 'baseline' retrieval system performance affects the overall opinion-finding performance. We apply two effective opinion-finding techniques to all the baseline runs submitted to the TREC 2007 Blog track, and draw new insights and conclusions.
- D. Hannah, C. Macdonald, B. He, J. Peng, and I. Ounis. University of Glasgow at TREC 2007: Experiments in Blog and Enterprise Tracks with Terrier. In Proceedings of TREC 2007.Google Scholar
- B. He, C. Macdonald, and I. Ounis. Ranking Opinionated Blog Posts using OpinionFinder. In Proceedings of SIGIR 2008. Google ScholarDigital Library
- C. Macdonald, I. Ounis, and I. Soboroff. Overview of the TREC 2007 Blog Track. In Proceedings of TREC 2007.Google Scholar
- I. Ounis, M. de Rijke, C. Macdonald, G. Mishne, and I. Soboroff. Overview of the TREC 2006 Blog Track. In Proceedings of TREC 2006.Google Scholar
- T. Wilson, P. Hoffmann, S. Somasundaran, J. Kessler, J. Wiebe, Y. Choi, C. Cardie, E. Riloff, and S. Patwardhan. OpinionFinder: a system for subjectivity analysis. In Proceedings of HLT/EMNLP on Interactive Demos, 2005. Google ScholarDigital Library
Index Terms
- Limits of opinion-finding baseline systems
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