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Fine-grained Subjectivity and Sentiment Analysis: Recognizing the intensity, polarity, and attitudes of private states

Wilson, Theresa Ann (2008) Fine-grained Subjectivity and Sentiment Analysis: Recognizing the intensity, polarity, and attitudes of private states. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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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.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Wilson, Theresa
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairWiebe, Janycewiebe@cs.pitt.eduJMW106
Committee MemberLitman, Dianelitman@cs.pitt.eduDLITMAN
Committee MemberAshley, Kevinashley@pitt.eduASHLEY
Committee MemberHwa, Rebeccahwa@cs.pitt.eduREH23
Date: 16 June 2008
Date Type: Completion
Defense Date: 4 May 2007
Approval Date: 16 June 2008
Submission Date: 23 April 2008
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Intelligent Systems
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Attitudes; Opinions; Private States; Sentiment; Subjectivity
Other ID:, etd-04232008-124057
Date Deposited: 10 Nov 2011 19:41
Last Modified: 15 Nov 2016 13:42


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