TextTiling: segmenting text into multi-paragraph subtopic passages
Computational Linguistics
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
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
Thumbs up?: sentiment classification using machine learning techniques
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
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
Identifying and analyzing judgment opinions
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Just how mad are you? finding strong and weak opinion clauses
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Multilingual subjectivity analysis using machine translation
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Lydia: a system for large-scale news analysis
SPIRE'05 Proceedings of the 12th international conference on String Processing and Information Retrieval
| Hi-index | 0.00 |
This paper contrasts the content and form of objective versus subjective texts. A collection of on-line newspaper news items serve as objective texts, while parliamentary speeches (debates) and blog posts form the basis of our subjective texts, all in Portuguese. The aim is to provide general linguistic patterns as used in objective written media and subjective speeches and blog posts, to help construct domain-independent templates for information extraction and opinion mining. Our hybrid approach combines statistical data along with linguistic knowledge to filter out irrelevant patterns. As resources for subjective classification are still limited for Portuguese, we use a parallel corpus and tools developed for English to build our subjective spoken corpus, through annotations produced for English projected onto a parallel corpus in Portuguese. A measure for the saliency of n-grams is used to extract relevant linguistic patterns deemed "objective" and "subjective". Perhaps unsurprisingly, our contrastive approach shows that, in Portuguese at least, subjective texts are characterized by markers such as descriptive, reactive and opinionated terms, while objective texts are characterized mainly by the absence of subjective markers.