Exploiting subjectivity classification to improve information extraction

Journal ArticleInformation extraction (IE) systems are prone to false hits for a variety of reasons and we observed that many of these false hits occur in sentences that contain subjective language (e.g., opinions, emotions, and sentiments). Motivated by these observations, we explore the idea of using subjectivity analysis to improve the precision of information extraction systems. In this paper, we describe an IE system that uses a subjective sentence classifier to filter its extractions. We experimented with several different strategies for using the subjectivity classifications, including an aggressive strategy that discards all extractions found in subjective sentences and more complex strategies that selectively discard extractions. We evaluated the performance of these different approaches on the MUC-4 terrorism data set. We found that indiscriminately filtering extractions from subjective sentences was overly aggressive, but more selective filtering strategies improved IE precision with minimal recall loss

Learning subjective nouns using extraction pattern bootstrapping

Journal ArticleWe explore the idea of creating a subjectivity classifier that uses lists of subjective nouns learned by bootstrapping algorithms. The goal of our research is to develop a system that can distinguish subjective sentences from objective sentences. First, we use two bootstrapping algorithms that exploit extraction patterns to learn sets of subjective nouns. Then we train a Naive Bayes classifier using the subjective nouns, discourse features, and subjectivity clues identified in prior research. The bootstrapping algorithms learned over 1000 subjective nouns, and the subjectivity classifier performed well, achieving 77% recall with 81% precision

Recognizing and organizing opinions expressed in the world press

Journal ArticleTomorrow's question answering systems will need to have the ability to process information about beliefs, opinions, and evaluations-the perspective of an agent. Answers to many simple factual questions-even yes/no questions-are affected by the perspective of the information source. For example, a questioner asking question (1) might be interested to know that, in general, sources in European and North American governments tend to answer "no" to question (1), while sources in African governments tend to answer "yes:

Word Sense and Subjectivity

This paper discusses word sense and subjectivity

Multilingual Subjectivity: Are More Languages Better?

This paper discusses multilingual subjectivity

A Bootstrapping Method for Building Subjectivity Lexicons for Languages with Scarce Resources

This article discusses a bootstrapping method for building subjectivity lexicons for languages with scarce resources

Subjectivity Word Sense Disambiguation

This paper investigates a new task, subjectivity word sense disambiguation (SWSD), which is to automatically determine which word instances in a corpus are being used with subjective senses, and which are being used with objective senses

Learning Multilingual Subjective Language via Cross-Lingual Projections

This paper discusses learning multilingual subjective language via cross-lingual projections