Sentiment and Subjectivity in Text
Workshop at the Annual Meeting of
the Association of Computational Linguistics (ACL 2006)
Sydney, Australia
July 22
** Submission Deadline: April 7,
2006 **
Description:
Sentiment and subjectivity in text constitute a problem that
is orthogonal to typical topic detection tasks in text classification. Despite
the lack of a precise definition of sentiment or subjectivity, headway has been
made in matching human judgments by automatic means. Such systems can prove
useful in a variety of contexts. In many applications it is important to
distinguish what an author is talking about from his or her subjective stance
towards the topic. If the writing is highly subjective, as for example in an
editorial text or comment, the text should be treated differently than if it
were a mostly objective presentation of facts, as for example in a newswire.
Information extraction, summarization, and question answering can benefit from
an accurate separation of subjective content from objective content.
Furthermore, the particular sentiment expressed by an author towards a topic is
important for "opinion mining", i.e. the extraction of prevalent
opinions about topics or items from a collection of texts. Similarly, in business
intelligence it is important to automatically extract positive and negative
perceptions about features of a product or service.
Over the past several years, there has
been an increasing number of publications focused on the detection and
classification of sentiment and subjectivity in text.
The purpose of this workshop is to bring together
researchers to share recent work in this area.
Workshop participants and contributors are expected to come
from various areas of research: Information Retrieval, Question Answering, Text
Categorization, Machine Learning, etc.
Topics of interest include, but are not limited to:
- relevance
of sentiment and subjectivity detection for question answering,
information retrieval, and opinion mining
- detection
of sentiment strength
- supervised,
weakly supervised and unsupervised learning techniques for sentiment and
subjectivity detection
- automatic
and semi-automatic discovery of subjectivity and sentiment indicators
- feature
analysis and feature selection for sentiment and subjectivity detection:
bag-of-words approaches and beyond
- topic-independent
subjectivity and sentiment identification
- identification
of the target of subjective and sentiment expressions
- attribution
of opinion and sentiment
- sentiment/subjectivity
corpora and annotation
- sentiment
lexica
- discourse
analysis and subjectivity/sentiment
- applications
of sentiment and subjectivity analysis, such as
o
text filtering
o
tracking public opinion over time
o
analysis of survey responses
o
automated chat systems (chatbots)
and responsive characters in software games
o
customer relation management
o
summarization of reviews
IMPORTANT DATES AND DEADLINES
Paper submission deadline: April 7, 2006
Notification of acceptance: May 15, 2006
Camera ready copy: June 6, 2006
List of accepted papers:
Click here.
NEW: Schedule
Click here.
INVITED TALKS
There are two invited talks, representing an industry and an academic perspective on the topic.
- Pero Subasic and Hadar Shemtov (Yahoo): Sentiment/Subjectivity Analysis - Industry Perspective.
- Bing Liu (University of Illinois at Chicago): Extracting and Summarizing Opinions on the Web.
NOTE TO PRESENTERS
We will post the final workshop schedule as soon as we have found a substitute/alternative arrangement for the canceled invited talk.
Talks are 20 minutes plus 7-10 minutes for questions/discussion. Standard AV equipment is available, so you can bring your own laptop.
ORGANIZERS
Michael Gamon (Microsoft Research)
Anthony Aue (Microsoft Research)
CONTACT
For questions, comments, etc. please send email to mgamon AT microsoft Dot com.
Program Committee:
Shlomo Argamon (Illinois Institute of Technology)
Claire Cardie (Cornell University)
Graeme Hirst (University of Toronto)
Eduard Hovy (USC Information Sciences Institute)
Aravind Joshi (University of Pennsylvania)
Jussi Karlgren (Swedish Institute of Computer Science)
Roy Lipski
Nicolas Nicolov (Umbria Inc.)
Bo Pang (Cornell)
Ana-Maria Popescu (University of Washington)
Dragomir Radev (University of Michigan)
Maarten de Rijke
(University of Amsterdam)
Franco Salvetti (Umbria Inc.)
Marc Schröder
(DFKI)
Michael Strube
(EML Research)
Pero Subasic
(Yahoo Inc.)
Peter Turney (National Research
Council Canada)
Özlem Uzuner (Massachusetts
Institute of Technology)
Casey Whitelaw (University of Sydney)
Janyce Wiebe (University of Pittsburgh)
