Private states (mental and emotional states) are part of the information that is conveyed in many forms of discourse. News articles often report emotional responses to news stories; editorials, reviews, and weblogs convey opinions and beliefs. This dissertation investigates the manual and automatic identification of linguistic expressions of private states in a corpus of news documents from the world press. A term for the linguistic expression of private states is subjectivity.
The conceptual representation of private states used in this dissertation is that of Wiebe et al. (2005). As part of this research, annotators are trained to identify expressions of private states and their properties, such as the source and the intensity of the private state. This dissertation then extends the conceptual representation of private states to better model the attitudes and targets of private states. The inter-annotator agreement studies conducted for this dissertation show that the various concepts in the original and extended representation of private states can be reliably annotated.
Exploring the automatic recognition of various types of private states is also a large part of this dissertation. Experiments are conducted that focus on three types of fine-grained subjectivity analysis: recognizing the intensity of clauses and sentences, recognizing the contextual polarity of words and phrases, and recognizing the attribution levels where sentiment and arguing attitudes are expressed. Various supervised machine learning algorithms are used to train automatic systems to perform each of these tasks. These experiments result in automatic systems for performing fine-grained subjectivity analysis that significantly outperform baseline systems.
Identifer | oai:union.ndltd.org:PITT/oai:PITTETD:etd-04232008-124057 |
Date | 16 June 2008 |
Creators | Wilson, Theresa Ann |
Contributors | Rebecca Hwa, Janyce Wiebe, Diane Litman, Kevin Ashley |
Publisher | University of Pittsburgh |
Source Sets | University of Pittsburgh |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | http://etd.library.pitt.edu/ETD/available/etd-04232008-124057/ |
Rights | unrestricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to University of Pittsburgh or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
Page generated in 3.7578 seconds