Recognizing contextual polarity in phrase-level sentiment analysis
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Multi-perspective question answering using the OpQA corpus
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Opinion Question Answering: Towards a Unified Approach
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Going beyond traditional QA systems: challenges and keys in opinion question answering
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Evaluating EmotiBlog robustness for sentiment analysis tasks
NLDB'11 Proceedings of the 16th international conference on Natural language processing and information systems
Mining slang and urban opinion words and phrases from cQA services: an optimization approach
Proceedings of the fifth ACM international conference on Web search and data mining
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The importance of the new textual genres such as blogs or forum entries is growing in parallel with the evolution of the Social Web. This paper presents two corpora of blog posts in English and in Spanish, annotated according to the EmotiBlog annotation scheme. Furthermore, we created 20 factual and opinionated questions for each language and also the Gold Standard for their answers in the corpus. The purpose of our work is to study the challenges involved in a mixed fact and opinion question answering setting by comparing the performance of two Question Answering (QA) systems as far as mixed opinion and factual setting is concerned. The first one is open domain, while the second one is opinion-oriented. We evaluate separately the two systems in both languages and propose possible solutions to improve QA systems that have to process mixed questions.