Development and use of a gold-standard data set for subjectivity classifications
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Learning subjective nouns using extraction pattern bootstrapping
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Learning extraction patterns for subjective expressions
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
A sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
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
OpinionFinder: a system for subjectivity analysis
HLT-Demo '05 Proceedings of HLT/EMNLP on Interactive Demonstrations
Generating a non-English subjectivity lexicon: relations that matter
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Multilingual subjectivity analysis using machine translation
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Using bilingual knowledge and ensemble techniques for unsupervised Chinese sentiment analysis
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Bootstrapping subjectivity detection
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Filling the gap: semi-supervised learning for opinion detection across domains
CoNLL '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning
A cross-corpus study of unsupervised subjectivity identification based on calibrated EM
WASSA '11 Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis
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Subjectivity tagging is a prior step for sentiment annotation. Both machine learning based approaches and linguistic knowledge based ones profit from using subjectivity lexicons. However, most of these kinds of resources are often available only for English or other major languages. This work analyses two strategies for building subjectivity lexicons in an automatic way: by projecting existing subjectivity lexicons from English to a new language, and building subjectivity lexicons from corpora. We evaluate which of the strategies performs best for the task of building a subjectivity lexicon for a less-resourced language (Basque). The lexicons are evaluated in an extrinsic manner by classifying subjective and objective text units belonging to various domains, at document- or sentence-level. A manual intrinsic evaluation is also provided which consists of evaluating the correctness of the words included in the created lexicons.