28.2178, Calls: Computational Linguistics/Denmark
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LINGUIST List: Vol-28-2178. Tue May 09 2017. ISSN: 1069 - 4875.
Subject: 28.2178, Calls: Computational Linguistics/Denmark
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Date: Tue, 09 May 2017 13:57:11
From: Saif Mohammad [uvgotsaif at gmail.com]
Subject: 8th Workshop on Computational Approaches to Subjectivity
Full Title: 8th Workshop on Computational Approaches to Subjectivity
Short Title: WASSA 2017
Date: 08-Sep-2017 - 08-Sep-2017
Location: Copenhagen, Denmark
Contact Person: Saif Mohammad
Meeting Email: saif.mohammad at nrc-cnrc.gc.ca
Web Site: http://optima.jrc.it/wassa2017/
Linguistic Field(s): Computational Linguistics
Call Deadline: 10-Jun-2017
Meeting Description:
The 8th Workshop on Computational Approaches to Subjectivity, Sentiment and
Social Media Analysis (WASSA 2017) will be held in conjunction with
EMNLP-2017. Its aim is to continue the line of the previous editions, bringing
together researchers in Computational Linguistics working on Subjectivity and
Sentiment Analysis and researchers working on interdisciplinary aspects of
affect computation from text. Additionally, starting with WASSA 2013, we
extended the focus to Social Media phenomena and the impact of affect-related
phenomena in this context.
In 2017, we also include two shared tasks on emotions as part of the workshop.
New labeled training and test data will be provided and participants can test
their automatic systems on this common dataset. Papers describing the systems
will be presented at the WASSA workshop, either as oral presentations (top
scoring systems) or as posters.
Research in automatic Subjectivity and Sentiment Analysis (SSA), as subtasks
of Affective Computing and Natural Language Processing (NLP), has flourished
in the past years. The growth in interest in these tasks was motivated by the
birth and rapid expansion of the Social Web that made it possible for people
all over the world to share, comment or consult content on any given topic. In
this context, opinions, sentiments and emotions expressed in Social Media
texts have been shown to have a high influence on the social and economic
behaviour worldwide. SSA systems are highly relevant to many real-world
applications (e.g. marketing, eGovernance, business intelligence, social
analysis, public health) and also many tasks in NLP – information extraction,
question answering, textual entailment, to name just a few.
The importance of this field has been proven by the high number of approaches
proposed in research in the past decade, as well as by the interest that it
raised from other disciplines (Economics, Sociology, Psychology, Marketing,
Crisis Management, Behavioral Studies) and the applications that were created
using its technology.
In spite of the growing body of research in the area in the past years,
dealing with affective phenomena in text has proven to be a complex,
interdisciplinary problem that remains far from being solved. Its challenges
include the need to address the issue from different perspectives, at
different levels, and different modalities, depending on the characteristics
of the textual genre, the language(s) treated and the final application for
which the analysis is done. Additionally, SSA from Social Media texts has
opened the way to many other types of analyses, linking textual data with
images, social network metadata and social-media-specific text markings (e.g.
Twitter hashtags).
Finally, the possibility to follow trends on opinions, while comparing and
contrasting different sources of information (e.g. mainstream media vs. social
media) allows for a more complete view and fairer opinion formation process.
Contact:
- Alexandra Balahur: alexandra.balahur at jrc.ec.europa.eu
- Saif M. Mohammad: saif.mohammad at nrc-cnrc.gc.ca
- Erik van der Goot: Erik.van-der-Goot at jrc.ec.europa.eu
2nd Call for Papers:
In this new proposed edition, we would like to encourage the submission of
long and short research and demo papers including, but not restricted to the
following topics related to subjectivity and sentiment analysis:
- Resources for subjectivity, sentiment and social media analysis;
(semi-)automatic corpora generation and annotation
- Opinion retrieval, extraction, categorization, aggregation and summarization
- Trend detection in social media using subjectivity and sentiment analysis
techniques
- Data linking through social networks based on affect-related NLP methods
- Impact of affective data from social media
- Mass opinion estimation based on NLP and statistical models
- Online reputation management
- Topic and sentiment studies and applications of topic-sentiment analysis
- Domain, topic and genre dependency of sentiment analysis
- Ambiguity issues and word sense disambiguation of subjective language
- Pragmatic analysis of the opinion mining task
- Use of Semantic Web technologies for subjectivity and sentiment analysis
- Improvement of NLP tasks using subjectivity and/or sentiment analysis
- Intrinsic and extrinsic evaluations subjectivity and sentiment analysis
- Subjectivity, sentiment and emotion detection in social networks
- Classification of stance in dialogues
- Applications of sentiment and social media analysis systems
- Application of theories from other related fields (Neuropsychology,
Cognitive Science, Psychology) to subjectivity and sentiment analysis
- Visualizing affect in traditional text sources as well as social media posts
Long Papers:
Long papers may consist of up to eight (8) pages of content, with two (2)
additional pages of references, and will be presented orally.
Short Papers:
Short papers may consist of up to five (5) pages of content, and two (2)
additional pages of references. The following types of papers are appropriate
for a short paper submission:
- A paper describing the demonstration of a system
- A small, focused contribution
- Work in progress
- A negative result
- An opinion piece
- An interesting application nugget
Short papers will be presented either orally or as a poster. The choice of
presentation will be given not based on the quality of the submission, but on
the PC's recommendation relating to the most suitable presentation method.
Papers for WASSA should be submitted using the EMNLP 2017 Style Files,
available at: hhttp://emnlp2017.net/call-for-papers.html
Reviewing for WASSA 2017 will be blind: reviewers will not be presented with
the identity of paper authors. Authors should avoid writing anything that
makes their identity obvious in the text.
Submissions should be original, and in particular should not previously have
been formally published.
Accepted papers will be published in the EMNLP WASSA proceedings, with ISBN.
The best papers will be chosen for a special issue of an ISI-indexed journal
(to be confirmed). Past editions special issues include the Decision Support
Systems journal (Elsevier) and Computer Speech and Language journal
(Elsevier), Information Processing and Management (Elsevier).
To submit a paper, please access the WASSA 2017 submission link, which will be
announced soon.
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