Computing Attitude and Affect in Text: Theory and Applications / Edition 1

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Overview

The chapters in this book address attitude, affect, and subjective opinion. Various conceptual models and computational methods are presented, including distinguishing attitudes from simple factual assertions; distinguishing between the author’s reports from reports of other people’s opinions; and distinguishing between explicitly and implicitly stated attitudes. In addition, many applications are described that promise to benefit from the ability to understand attitudes and affect, such as indexing and retrieval of documents by opinion; automatic question answering about opinions; analysis of sentiment in the media and in discussion groups; analyzing client discourse in therapy and counseling; determining relations between scientific texts; generating more appropriate texts; and creating writers’ aids. In addition to English texts, the collection includes studies of French, Japanese, and Portuguese texts.

The chapters are extended and revised versions of papers presented at the American Association for Artificial Intelligence (AAAI) Spring Symposium on Exploring Attitude and Affect in Text, which took place in March 2004 at Stanford University. The symposium, and the book which grew out it, represent a first foray into this area and a balance among conceptual models, computational methods, and applications.

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Editorial Reviews

From the Publisher
From the reviews:

"The volume contains 24 extended versions of papers that were originally presented at the American Association for Artificial Intelligence (AAAI) … . should become an indispensable resource for anyone interested in this area. Whether the reader is more interested in the computational or the linguistic aspects of the problem-or even just the range of possible applications-this collection will broaden the perspective on the issue. For readers with no background in sentiment detection the volume can serve as an initial overview of the field … ." (Michael Gamon, Computational Linguistics, Vol. 33 (2), 2007)

"...this volume shines as truly presenting cutting-edge research in a specific subfield within NLP. The editors have done a fine job in aggregating full-length papers that are both interesting and informative from established researchers in the field." (from the ACM Reviews by Robert Goldberg, Queens College, NY, USA)

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Product Details

  • ISBN-13: 9781402040269
  • Publisher: Springer Netherlands
  • Publication date: 1/9/2006
  • Series: Information Retrieval Series , #20
  • Edition description: 2006
  • Edition number: 1
  • Pages: 342
  • Product dimensions: 9.21 (w) x 6.14 (h) x 0.81 (d)

Table of Contents

Preface *.- 1. Contextual Valence Shifters, Livia Polanyi, Annie Zaenen *.- 1. Introduction *.- 2. From Simple Valence to Contextually Determined Valence *.- 3. Contextual Valence Shifters *.- 4. Conclusion *.- 2. Conveying Attitude with Reported Speech, Sabine Bergler *.- 1. Introduction *.- 2. Evidential Analysis of Reported Speech *.- 3. Profile Structure *.- 4. Extended Example *.- 5. Source List Annotation *.- 6. Extension to Other Attribution *.- 7. Conclusion *.- 3. Where Attitudinal Expressions Get their Attitude, Jussi Karlgren, Gunnar Eriksson, Kristofer Franzén *.- 1. Research Questions to Motivate the Study of Attitudinal Expressions *.- 2. Starting Points – Prototypical Attitudinal Expressions *.- 3. Text Topicality: Players *.- 4. Text Topicality: Moves *.- 5. Identifying Players *.- 6. The Case for Animacy: Adjectival Attributes and Genitive Attributes *.- 7. The Case for Syntactic Structure: Situational Reference *.- 8. Using Syntactic Patterns more Systematically *.- 9. Generalizing from Syntactic Patterns to the Lexicon *.- 10. Conclusions *.- 4. Analysis of Linguistic Features Associated with Point of View for Generating Stylistically Appropriate Text, Nancy L. Green *.- 1. Introduction *.- 2. Perspectives in Corpus *.- 3. Associated Features *.- 4. Implications for Natural Language Generation and Automatic Recognition of Point of View *.- 5. The Subjectivity of Lexical Cohesion in Text, Jane Morris, Graeme Hirst *.- 1. Introduction *.- 2. Theoretical Background *.- 3. Experimental Study *.- 4. Discussion *.- 6. A Weighted Referential Activity Dictionary, Wilma Bucci, Bernard Maskit *.- 1. Introduction *.- 2. Methods *.- 3. Results *.- 7. Certainty Identification in Texts: Categorization Model and Manual Tagging Results, Victoria L. Rubin, Elizabeth D. Liddy, Noriko Kando *.- 1. Analytical Framework *.- 2. Proposed Certainty Categorization Model *.- 3. Empirical Study *.- 4. Applications *.- 5. Conclusions and Future Work *.- 8. Evaluating an Opinion Annotation Scheme Using a New Multi-Perspective Question and Answer Corpus, Veselin Stoyanov, Claire Cardie, Diane Litman, Janyce Wiebe *.- 1. Introduction *.- 2. Low-Level Perspective Information *.- 3. The MPQA NRRC Corpus *.- 4. Multi-Perspective Question and Answer Corpus Creation *.- 5. Evaluation of Perspective Annotations for MPQA *.- 6. Conclusions and Future Work *.- 9. Validating the Coverage of Lexical Resources for Affect Analysis and Automatically Classifying New Words along Semantic Axes, Gregory Grefenstette, Yan Qu, David A. Evans, James G. Shanahan *.- 1. Introduction *.- 2. The Current Clairvoyance Affect Lexicon *.- 3. Emotive Patterns *.- 4. Scoring the Intensity of Candidate Affect Words *.- 5. Future Work *.- 6. Conclusions *.- 10. A Computational Semantic Lexicon of French Verbs of Emotion, Yvette Yannick Mathieu *.- 1. Introduction *.- 2. Semantic Lexicon Description *.- 3. FEELING System *.- 4. Evaluation *.- 5. Related Work *.- 6. Conclusion *.- 11. Extracting Opinion Propositions and Opinion Holders using Syntactic and Lexical Cues, Steven Bethard, Hong Yu, Ashley Thornton, Vasileios Hatzivassiloglou, Dan Jurafsky *.- 1. Introduction *.- 2. Data *.- 3. Opinion-Oriented Words *.- 4. Identifying Opinion Propositions *.- 5. Results *.- 6. Error Analysis *.- 7. Discussion *.- 12. Approaches for Automatically Tagging Affect, Nathanael Chambers, Joel Tetreault, James Allen *.- 1. Introduction *.- 2. Background *.- 3. Rochester Marriage-Counseling Corpus *.- 4. Approaches to Tagging *.- 5. Evaluations *.- 6. Discussion *.- 7. CATS Tool *.- 8. Related Work *.- 9. Conclusion *.- 13. Argumentative Zoning for Improved Citation Indexing, Simone Teufel *.- 1. Citation Indexing and Citation Maps *.- 2. Argumentative Zoning and Author Affect *.- 3. Meta-discourse *.- 4. Human Annotation of Author Affect *.- 5. Features for Author Affect *.- 6. Evaluation *.- 7. Conclusion *.- 14. Politeness and bias in dialogue summarization: two exploratory studies, Norton Trevisan Roman, Paul Piwek, Ariadne Maria Brito Rizzoni Carvalho *.- 1. Introduction *.- 2. First Study: Politeness and Bias in Unconstrained Dialogue Summarization *.- 3. Second Study: Politeness and Bias in Constrained Dialogue Summarization *.- 4. Comparison *.- 5. Conclusion and Outlook *.- 15. Generating More-Positive and More-Negative Text, Diana Zaiu Inkpen, Ol’ga Feiguina, Graeme Hirst *.- 1. Near-Synonyms and Attitudinal Nuances *.- 2. Related Work *.- 3. Estimating the Relative Semantic Orientation of Text *.- 4. Word Sense Disambiguation *.- 5. Analysis *.- 6. Generation *.- 7. Experiments *.- 8. Evaluation *.- 9. Conclusion *.- 16. Identifying Interpersonal Distance using Systemic Features, Casey Whitelaw, Jon Patrick, Maria Herke-Couchman *.- 1. Introduction *.- 2. Systemic Functional Linguistics *.- 3. Representing System Networks *.- 4. Identifying .- gisters *.- 5. Conclusion *.- 17. Corpus-Based Study of Scientific Methodology: Comparing the Historical and Experimental Sciences, Shlomo Argamon, Jeff Dodick *.- 1. Introduction *.- 2. Background *.- 3. Systemic Indicators as Textual Features *.- 4. Experimental Study *.- 5. Example Texts *.- 6. Conclusions *.- 18. Argumentative Zoning Applied to Critiquing Novices’ Scientific Abstracts, Valéria D. Feltrim, Simone Teufel, Maria das Graças V. Nunes, Sandra M. Aluísio *.- 1. Introduction *.- 2. The SciPo System *.- 3. Argumentative Zoning for Portuguese Texts *.- 4. Evaluation of SciPo’s Critiquing Tool *. -5. Conclusions *.- 19. Using Hedges to Classify Citations in Scientific Articles, Chrysanne Di Marco, Frederick W. Kroon, Robert E. Mercer *.- 1. Scientific Writing, the Need for Affect, and Its Role in Citation Analysis *.- 2. Hedging in Scientific Writing *.- 3. Classifying Citations in Scientific Writing *.- 4. Determining the Importance of Hedges in Citation Contexts *.- 5. A Citation Indexing Tool for Biomedical Literature Analysis *.- 6. Conclusions and Future Work *.- 20. Towards a Robust Metric of Polarity, Kamal Nigam, Matthew Hurst *.- 1. Introduction *.- 2. Related Work *.- 3. Classes of Polar Expression *.- 4. Recognizing Polar Language *.- 5. Topic Detection in Online Messages *.- 6. The Intersection of Topic and Polarity *.- 7. Empirical Analysis *.- 8. Metrics for Topic and Polarity *.- 9. Conclusions and Future Work *.- 21. Characterizing Buzz and Sentiment in Internet Sources: Linguistic Summaries and Predictive Behaviors, Richard M. Tong, Ronald R. Yager *.- 1. Introduction and Motivation *.- 2. Linguistic Summaries *.- 3. Example Applications *.- 4. TRENDS-2™ Infrastructure *.- 5. Previous and Related Work *.- 6. Open R&D and Application Issues *.- 22. Good News or Bad News? Let the Market Decide, Moshe Koppel, Itai Shtrimberg *.- 1. Introduction *.- 2. Experiments *.- 3. Results *.- 4. Conclusions *.- 23. Opinion Polarity Identification of Movie Reviews, Franco Salvetti, Christoph Reichenbach, Stephen Lewis *.- 1. Introduction *.- 2. Related Research *.- 3. Probabilistic Approaches to Polarity Identification *.- 4. Features for Analysis *.- 5. Part of Speech Feature Selection *.- 6. Experiments *.- 7. Synonymy and Hypernymy Feature Generalization *.- 8. Selection by Ranking *.- 9. Discussion *.- 10. Conclusion *.- 24. Multi-Document Viewpoint Summarization Focused on Facts, Opinion and Knowledge, Yohei Seki, Koji Eguchi, Noriko Kando *.- 1. Introduction *.- 2. Experiment Overview: Multi-Document Viewpoint Summarization with Summary Types *.- 3. Sentence-type Annotation *.- 4. Genre Classification *.- 5. Experiment Results *.- 6. Conclusion *.- INDEX *

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