[DL] [CFP] ESWC-19 Challenge on Semantic Sentiment Analysis

Mauro Dragoni dragoni at fbk.eu
Wed Jan 2 11:13:34 CET 2019


ESWC-19 Challenge on Semantic Sentiment Analysis
==================================================================
Venue: Portoroz, Slovenia
Hashtag: #SentimentAnalysis
Conference Site: http://2019.eswc-conferences.org/
Challenge Site:
http://www.maurodragoni.com/research/opinionmining/events/challenge-2019/
Evaluation on the following tasks:
Polarity detection
Polarity Detection in presence of metaphorical language
Aspect-Based Sentiment Analysis
First submission deadline: Friday March 8th, 2019, 23:59 (CET)
==================================================================

The development of Web 2.0 has given users important tools and
opportunities to create, participate and populate blogs, review sites, web
forums, social networks and online discussions. Tracking emotions and
opinions on certain subjects allows identifying users’ expectations,
feelings, needs, reactions against particular events, political view
towards certain ideas, etc. Therefore, mining, extracting and understanding
opinion data from text that reside in online discussions is currently a hot
topic for the research community and a key asset for industry.

The produced discussion spanned a wide range of domains and different areas
such as commerce, tourism, education, health, etc. Moreover, this comes
back and feeds the Web 2.0 itself thus bringing to an exponential expansion.

This explosion of activities and data brought to several opportunities that
can be exploited in both research and industrial world. One of them
concerns the mining and detection of users’ opinions which started back in
2003 (with the classical problem of polarity detection) and several
variations have been proposed. Therefore, today there are still open
challenges that have raised interest within the scientific community where
new hybrid approaches are being proposed that, making use of new lexical
resources, natural language processing techniques and semantic web best
practices, bring substantial benefits.

Computer World [1] estimates that 70%-80% of all digital data consists of
unstructured content, much of which is locked away across a variety of
different data stores, locations and formats. Besides, accurately analyzing
the text in an understandable manner is still far from being solved as this
is extremely difficult. In fact, mining, detecting and assessing opinions
and sentiments from natural language involves a deep (lexical, syntactic,
semantic) understanding of most of the explicit and implicit, regular and
irregular rules proper of a language.

Existing approaches are mainly focused on the identification of parts of
the text where opinions and sentiments can be explicitly expressed such as
polarity terms, expressions, statements that express emotions. They usually
adopt purely syntactical approaches and are heavily dependent on the source
language and the domain of the input text. It follows that they miss many
language patterns where opinions can be expressed because this would
involve a deep analysis of the semantics of a sentence. Today, several
tools exist that can help understanding the semantics of a sentence. This
offers an exciting research opportunity and challenge to the Semantic Web
community as well. For example, sentic computing is a multi-disciplinary
approach to natural language processing and understanding at the crossroads
between affective computing, information extraction, and common-sense
reasoning, which exploits both computer and human sciences to better
interpret and process social information on the Web.

Therefore, the Semantic Sentiment Analysis Challenge looks for systems that
can transform unstructured textual information to structured machine
processable data in any domain by using recent advances in natural language
processing, sentiment analysis and semantic web.

By relying on large semantic knowledge bases, Semantic Web best practices
and techniques, and new lexical resources, semantic sentiment analysis
steps away from blind use of keywords, simple statistical analysis based on
syntactical rules, but rather relies on the implicit, semantics features
associated with natural language concepts. Unlike purely syntactical
techniques, semantic sentiment analysis approaches are able to detect
sentiments that are implicitly expressed within the text, topics referred
by those sentiments and are able to obtain higher performances than pure
statistical methods.

[1] Computer World, 25 October 2004, Vol. 38, NO 43.


*** Submissions ***

Two steps submission

* First step:

1. Abstract: no more than 200 words.
2. Paper (max 4 pages): containing the details of the system, including why
the system is innovative, which features or functions the system provides,
what design choices were made and what lessons were learned, how the
semantics has been employed and which tasks the system addresses.
Industrial tools with non disclosure restrictions are also allowed to
participate, and in this case they are asked to:
- explain even at a higher level their approach and engine
macro-components, why it is innovative, and how the semantics is involved;
    - provide free access (even limited) for research purposes to their
engine, especially to make repeatable the challenge results or other
experiments possibly included in their paper

* Second step (for accepted systems only)


1. Paper (max 15 pages): full description of the submitted system.
2. Web Access: applications should be either accessible via web or
downloadable or anyway a RESTful API must be provided to run the challenge
testset. If an application is not publicly accessible, password must be
provided for reviewers. A short set of instructions on how to use the
application or the RESTFul API must be provided as well.
3. The authors will have the possibility to present a poster and a demo
advertising their work or networking during a dedicated session.

Papers must comply with the LNCS style
Papers are submitted in PDF format via the EasyChair submission pages (
https://easychair.org/conferences/?conf=emsasw2019 remember to select the
topic Challenge)
Accepted papers will be published by Springer.
Extended versions of best systems will be invited to a journal special
issue (to be determined yet).
All the participants are invited to submit a paper containing the research
aspects of their systems to the ESWC 2017 Semantic Sentiment Analysis
Workshop (http://www.maurodragoni.com/research/opinionmining/events/)


*** Important dates ***

1. Friday March 8th, 2019, 23:59 (CET): First step submission
2. Monday April 8th, 2019, 23:59 (CET): Notification of acceptance
3. Tuesday April 23rd, 2019, 23:59 (CET): Camera ready papers for the
conference (4 pages max)
4. Tuesday May 21st, 2019, 23:59 (CET): Test data published
5. Friday May 24th, 2019, 23:59 (CET): Submission of test results
6. June 2rd – 6th, 2019: The Challenge takes place at ESWC-19
7. Friday July 5th, 2019: Camera ready paper for the challenge post
proceedings (15 pages document, tentative deadline)


*** Challenge Chairs ***
Erik Cambria
Mauro Dragoni
Diego Reforgiato Recupero

-- 
Dr. Mauro Dragoni
Researcher at Fondazione Bruno Kessler (FBK-IRST)
Via Sommarive 18, 38123, Povo, Trento, Italy
Tel. 0461-314053

########################################
Consider to submit a contribution to the
Knowledge and Language Processing track @ ACM SAC 2019
https://klp.fbk.eu <https://coco.fbk.eu/sac2018/>
Limassol, Cyprus, April 8-12, 2019
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