Call For Paper: Semantic Sentiment Analysis Workshop @ESWC2017.
Dates: May 28th 2017
Venue: Portoroz, Slovenia
Conference Site: http://2017.eswc-conferences.org/
Workshop Site: http://www.maurodragoni.com/research/opinionmining/events/
As the Web rapidly evolves, people are becoming increasingly enthusiastic
about interacting, sharing, and collaborating through social networks,
online communities, blogs, wikis, and the like. In recent years, this
collective intelligence has spread to many different areas, with particular
focus on fields related to everyday life such as commerce, tourism,
education, and health, causing the size of the social Web to expand
To identify the emotions (e.g. sentiment polarity, sadness, happiness,
anger, irony, sarcasm, etc.) and the modality (e.g. doubt, certainty,
obligation, liability, desire, etc.) expressed in this continuously growing
content is critical to enable the correct interpretation of the opinions
expressed or reported about social events, political movements, company
strategies, marketing campaigns, product preferences, etc.
This has raised growing interest both within the scientific community, by
providing it with new research challenges, as well as in the business
world, as applications such as marketing and financial prediction would
gain remarkable benefits.
One of the main application tasks in this context is opinion mining ,
which is addressed by a significant number of Natural Language Processing
techniques, e.g. for distinguishing objective from subjective statements
, as well as for more fine-grained analysis of sentiment, such as
polarity and emotions . Recently, this has been extended to the
detection of irony, humor, and other forms of figurative language . In
practice, this has led to the organisation of a series of shared tasks on
sentiment analysis, including irony and figurative language detection
(SemEval 2013, 2014, 2015, 2016), with the production of annotated data and
development of running systems.
However, existing solutions still have many limitations leaving the
challenge of emotions and modality analysis still open. For example, there
is the need for building/enriching semantic/cognitive resources for
supporting emotion and modality recognition and analysis. Additionally, the
joint treatment of modality and emotion is, computationally, trailing
behind, and therefore the focus of ongoing, current research. Also, while
we can produce rather robust deep semantic analysis of natural language, we
still need to tune this analysis towards the processing of sentiment and
modalities, which cannot be addressed by means of statistical models only,
currently the prevailing approaches to sentiment analysis in NLP. The
hybridization of NLP techniques with Semantic Web technologies is therefore
a direction worth exploring, as recently shown in [4, 5, 6, 7].
Based on the lessons learnt from the first edition, this year the scope of
the workshop is a bit broader (although still focusing on a very specific
domain) and accepted submissions will include abstracts and position papers
in addition to full papers. The workshops main focus will be discussion
rather than presentations, which are seen as seeds for boosting discussion
topics, and an expected result will be a joint manifesto and a research
roadmap that will provide the Semantic Web community with inspiring
The Workshop will be connected to the ESWC 2017 Semantic Sentiment Analysis
Challenge at ESWC2017 (https://github.com/diegoref/SSAC2017). Both the
Workshop and the Challenge can benefit from a Google Group, called Semantic
Sentiment Analysis Initiative. Please post messages related to the Workshop
under the discussion “ESWC 2017 Workshop on Emotions, Modality, Sentiment
Analysis and the Semantic Web.”
*** Topics of interest ***
Includes but not limited to:
* Ontologies and knowledge bases for emotion recognition
* Topic and entity based emotion recognition
* Semantics in the evolution of emotions within and across social media
systems and topics
* Semantic processing of social media for emotion recognition
* Contextualised emotion recognition
* Comparison of semantic approaches for emotion recognition
* Personalised semantic emotion recognition and monitoring
* Using semantics for prediction of emotions towards events, people,
* Baselines and datasets for semantic emotion recognition
* Semantics in stream-based emotion recognition
* Comparison between semantic and non-semantic approaches for emotion
* Multimodal emotion recognition
* Multilingual sentiment analysis
* Challenges in using semantics for emotion recognition
* Retrieval of emotion-based documents from repositories
* Deep learning and knowledge-enabled approaches for sentiment analysis
*** Submissions ***
Submission criteria are the following:
* Papers must comply with the LNCS style
* Full research papers (up to 8-10 pages)
* Short research papers (up to 4-6 pages)
* Position papers (2 pages)
Papers are submitted in PDF format via the workshop’s EasyChair submission
pages (https://easychair.org/conferences/?conf=emsasw2017 remember to
select the topic Workshop)
Accepted papers will be published by CEUR–WS. The best paper (according to
the reviewers’ rate) will be published within the main conference
We already sent a form request to Springer to include Workshop papers in a
Springer book. If the answer is positive (we should know this by mid March
2016) then the accepted papers will be published within the Springer book
and not CEUR-WS.
At least one of the authors of the accepted papers must register for the
workshop (pre-conference only option) to be included into the workshop
*** Important dates ***
March 3, 2017, 23:59 CET: Full, Short, and Position papers submission
March 31, 2017, 23:59 CET: Notification of acceptance
April 13, 2017, 23:59 CET: Camera-ready paper due
ESWC 2017 Workshop day: May 28, 2017 the whole day
*** Workshop Chairs ***
Diego Reforgiato Recupero
*** References ***
 Bo, P., and Lee, L. (2008). Opinion mining and sentiment analysis.
Foundations and Trends in Information Retrieval , 2 (1-2), 1-135.
 Wiebe, J., and Ellen, R. (2005). Creating Subjective and Objective
Sentence Classifiers from Unannotated Texts. Computational Linguistics and
Intelligent Text Processing 6th International Conference, CICLing (pp.
486-497). Mexico City: Springer.
 Paula, C., Sarmento, L., Silva, M. J., and de Oliveira, E. (2009).
Clues for detecting irony in user-generated contents: oh…!! it’s so
easy;-). Proceedings of the 1st international CIKM workshop on
Topic-sentiment analysis for mass opinion (pp. 53-56). ACM.
 Reforgiato Recupero, D., Presutti, V., Consoli, S., and Gangemi, A.
(2014). Sentilo: Frame-Based Sentiment Analysis. Cognitive Computation ,
 Saif, H., He, Y., and Alani, H. (2012). Semantic sentiment analysis of
Twitter. 11th International Semantic Web Conference (ISWC 2012) (pp.
 Gangemi, A., Presutti, V., and Reforgiato Recupero, D. (2014). Frame-
based detection of opinion holders and topics: a model and a tool. IEEE
Computational Intelligence , 9 (1), 20-30.
 Cambria, E., and Hussain, A. (2012). Sentic Computing: Techniques,
Tools, and Applications. Springer.
 Liu, B. (2012). Sentiment Analysis and Opinion Mining. Synthesis
Lectures on Human Language Technologies. Chicago: Morgan & Claypool
Dr. Mauro Dragoni
Researcher at Fondazione Bruno Kessler (FBK-IRST)
Via Sommarive 18, 38123, Povo, Trento, Italy
Cognitive Computing track @ ACM SAC 2017
Marrakech, Morocco, April 3-7, 2017
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