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LINGUIST List 25.2141

Wed May 14 2014

Calls: Cognitive Sci, Philosophy of Lang, Ling & Lit, Psycholing, Pragmatics/Canada

Editor for this issue: Anna White <awhitelinguistlist.org>

Date: 14-May-2014
From: Laura Kertz <laura_kertzbrown.edu>
Subject: Workshop: Can Cognitive Scientists Help Computers Recognize Irony?
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Full Title: Workshop: Can Cognitive Scientists Help Computers Recognize Irony?
Short Title: Irony at CogSci 2014

Date: 23-Jul-2014 - 23-Jul-2014
Location: Quebec City, Canada
Contact Person: Laura Kertz
Meeting Email: < click here to access email >
Web Site: https://sites.google.com/a/brown.edu/irony/

Linguistic Field(s): Cognitive Science; Ling & Literature; Philosophy of Language; Pragmatics; Psycholinguistics

Call Deadline: 07-Jun-2014

Meeting Description:

Irony is an important rhetorical device that takes many forms. The successful ironist effectively communicates something other than (and often opposite to) what he or she has literally said. Historically, the ironic voice has been studied by researchers in philosophy, language, social cognition and cognitive science. More recently, the problem of automatically detecting irony has garnered attention from computer scientists working in machine learning (ML) and natural language processing (NLP).

But classifying utterances as ironic has proven uniquely difficult. The standard ML approach to text classification is the 'bag-of-words' approach. With a sufficient amount of manually categorized examples (i.e., training data), such models can be extremely successful in a variety of classification tasks, e.g., spam filtering. But irony detection has proven to be much harder. Our view is that cognitive scientists may have much to offer computer science researchers interested in this problem.

Capitalizing on the co-location of CogSci with AAAI, this workshop thus aims to bring cognitive and computer scientists together to explore novel models for irony detection. In particular, we believe that developing representations of speakers and contexts and building models that factor these representations into judgments of utterances may drastically improve automated irony detection.

Call for Papers:

We are interested in submissions that explore the use, recognition and comprehension of irony from cognitive science and computer science perspectives. Topics of interest include, but are not limited to:

- Theories of irony and its function
- Classification methods for irony detection
- Descriptions of language resources (corpora) available
- Novel proposals for how computers might better recognize ironic intent
- Social aspects of irony

Abstracts should not be longer than 2 pages and should be sent directly to ironybrown.edu by 6/7/2014. Works in progress, new language resources and proposals describing potential novel directions/approaches to irony detection are all welcome.



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