Table of Contents

Contextual Valence Shifters.- Conveying Attitude with Reported Speech.- Where Attitudinal Expressions Get their Attitude.- Analysis of Linguistic Features Associated with Point of View for Generating Stylistically Appropriate Text.- The Subjectivity of Lexical Cohesion in Text.- A Weighted Referential Activity Dictionary.- Certainty Identification in Texts: Categorization Model and Manual Tagging Results.- Evaluating an Opinion Annotation Scheme Using a New Multi-Perspective Question and Answer Corpus.- Validating the Coverage of Lexical Resources for Affect Analysis and Automatically Classifying New Words along Semantic Axes.- A Computational Semantic Lexicon of French Verbs of Emotion.- Extracting Opinion Propositions and Opinion Holders using Syntactic and Lexical Cues.- Approaches for Automatically Tagging Affect: Steps Toward an Effective and Efficient Tool.- Argumentative Zoning for Improved Citation Indexing.- Politeness and Bias in Dialogue Summarization: Two Exploratory Studies.- Generating More-Positive and More-Negative Text.- Identifying Interpersonal Distance using Systemic Features.- Corpus-Based Study of Scientific Methodology: Comparing the Historical and Experimental Sciences.- Argumentative Zoning Applied to Critiquing Novices’ Scientific Abstracts.- Using Hedges to Classify Citations in Scientific Articles.- Towards a Robust Metric of Polarity.- Characterizing Buzz and Sentiment in Internet Sources: Linguistic Summaries and Predictive Behaviors.- Good News or Bad News? Let the Market Decide.- Opinion Polarity Identification of Movie Reviews.- Multi-Document Viewpoint Summarization Focused on Facts, Opinion and Knowledge.

Reviews

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)