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_kertz
brown.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 irony
brown.edu by 6/7/2014. Works in
progress, new language resources and proposals
describing potential novel
directions/approaches to irony detection are
all welcome.
Page Updated: 14-May-2014