OpinionFinder: a system for subjectivity analysis
HLT-Demo '05 Proceedings of HLT/EMNLP on Interactive Demonstrations
Ranking opinionated blog posts using OpinionFinder
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Adaptive subjective triggers for opinionated document retrieval
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Integrating Proximity to Subjective Sentences for Blog Opinion Retrieval
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Proximity-based opinion retrieval
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Information Retrieval on the Blogosphere
Foundations and Trends in Information Retrieval
Aggregation Methods for Proximity-Based Opinion Retrieval
ACM Transactions on Information Systems (TOIS)
Exploiting syntactic and semantic relationships between terms for opinion retrieval
Journal of the American Society for Information Science and Technology
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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.