SEMOD2015

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Revision as of 14:48, 17 January 2015


Emotions, Modality and the Semantic Web (SEMOD 2015)

at ESWC2015, Portoroz, Slovenia, 31th May - 4th June, 2015


Contents

Motivation and relevance for the Semantic Web community

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 exponentially.

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 (Bo & Lee, 2008), which is addressed by a significant number of Natural Language Processing techniques, e.g. for distinguishing objective from subjective statements (Wiebe & Ellen, 2005), as well as for more fine-grained analysis of sentiment, such as polarity and emotions (Liu, 2012). Recently, this has been extended to the detection of irony, humor, and other forms of figurative language (Paula, Sarmento, Silva, & de Oliveira, 2009, Reyes, Rosso, & Buscaldi, 2012). 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), 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 (ref to moma workshop? maybe not). 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 (Reforgiato Recupero, Presutti, Consoli, & Gangemi, 2014), (Saif, He, & Alani, 2012), (Gangemi, Presutti, & Reforgiato Recupero, 2014) and (Cambria & Hussain, 2012).

This workshop intends to be a discussion forum gathering researchers from Cognitive Linguistics, NLP, Semantic Web, and related areas for presenting their ideas on the relation between Semantic Web and the study of emotions and modalities.



Topics of Interest

Includes but not limited to:

  • Ontologies and knowledge bases for sentiment analysis
  • Topic and entity based sentiment analysis
  • Evolution of sentiment within and across social media systems and topics
  • Entity-based sentiment analysis
  • Semantic processing of social media for sentiment analysis
  • Contextualised sentiment analysis
  • Comparison of semantic approaches for sentiment analysis
  • Personalised sentiment analysis and monitoring
  • Prediction of sentiment towards events, people, organisations, etc.
  • Baselines and datasets for semantic sentiment analysis


Workshop format

Opinion mining, sentiment analysis, analysis of emotions and modalities are popular topics in the Natural Language Processing and Linguistics research fields. Regular workshops and challenges (shared tasks) on these themes are organized as co-located events with major conferences, such as IJCAI and ACL. Another recently organized related event is the MOMA (Models for Modality Annotation), a workshop that will be held in London (April 2015) in conjunction with the International Conference on Computational Semantics (IWCS 2015). Our workshop intends to complement these events, focusing on the relation between these topics and the Semantic Web.

This workshop proposal is a follow-up of ESWC 2014 workshop on “Semantic Web and Sentiment Analysis”. Following last year experience we propose a half day event. Although last year edition received a low number of paper submissions, the workshop was very successful in terms of participation, with an average of 20 attendees, excluding the organizers.

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 workshop’s 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 research challenges.

After a possible keynote presentation (of about 30 minutes), there will be a slot dedicated to long paper presentations (max 10 minutes each including questions). The rest of time will be dedicated to discussion leaving 15 minutes for a wrap-up session.

During the discussion session, contributors will have a short time to introduce their statements (from abstracts and position papers), which will be followed by discussion moderated by one of the chairs. A scriber will be nominated to take the minutes of the discussion, which will be the input of a joint manifesto.

Last but not least, should this workshop proposal and a challenge proposal related to the semantic sentiment analysis be accepted at ESWC 2015, the two events will have several interconnections and the workshop, following the same experience of the last year, will definitely include a talk from the submitted system to the challenge.


Submissions

Submissions must comply with the Springer LNCS style and will be made using

Authors are invited to submit:

  • Full papers (up to 8 pages)
  • Short and position papers (up to 4 pages)

Accepted papers will be published by CEUR--WS.

At least one of the authors of the accepted papers must register for both the main conference and the workshop to be included into the workshop proceedings.

Important dates

  • Submission deadline : to be defined
  • Notifications: to be defined
  • Camera ready version: to be defined

Workshop chairs:


Program Committee:

  • Erik Cambria, Nanyang Technological University, SG
  • Paolo Rosso, Universidad Politecnica de Valencia, ES
  • Harith Alani, KMI-OU, UK
  • Paul Buitelaar, DERI Galway, IR
  • Bebo White, University of Stanford, US
  • Fabio Ciravegna, University of Sheffield, UK
  • Eneko Agirre, University of the Basque Country, ES
  • Davide Buscaldi, Université Paris 13, Sorbonne Cité, CNRS, FR
  • Carlo Strapparava, FBK, IT
  • Diana Maynard, University of Sheffield (to be confirmed)
  • Viviana Patti, University of Turin (to be confirmed)
  • Valerio Basile, University of Groningen (to be confirmed)
  • J. Fernando Sánchez-Rada, Universidad Politecnica de Madrid, ES
  • Björn Schuller, Imperial College London, UK
  • Catherine Havasi, MIT, US
  • V. S. Subrahmanian, University of Maryland, US (to be confirmed)
  • William H. Hsu, University of Kansas State, US
  • Yulan He, Aston University, UK (to be confirmed)
  • Chenghua Lin, University of Aberdeen (to be confirmed)

Relevant References

  1. Wiebe, J., & 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.
  2. Bo, P., & Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval , 2 (1-2), 1-135.
  3. Cambria, E., & Hussain, A. (2012). Sentic Computing: Techniques, Tools, and Applications. Springer.
  4. Gangemi, A., Presutti, V., & Reforgiato Recupero, D. (2014). Frame-based detection of opinion holders and topics: a model and a tool. IEEE Computational Intelligence , 9 (1), 20-30.
  5. Liu, B. (2012). Sentiment Analysis and Opinion Mining. Synthesis Lectures on Human Language Technologies. Chicago: Morgan & Claypool Publishers.
  6. Paula, C., Sarmento, L., Silva, M. J., & 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.
  7. Saif, H., He, Y., & Alani, H. (2012). Semantic sentiment analysis of Twitter. 11th International Semantic Web Conference (ISWC 2012) (pp. 508-524). Springer.
  8. Reyes, A., Rosso, P., & Davide, B. (2012). From humor recognition to irony detection: The figurative language of social media. Data & Knowledge Engineering , 74, 1-12.
  9. Reforgiato Recupero, D., Presutti, V., Consoli, S., & Gangemi, A. (2014). Sentilo: Frame-Based Sentiment Analysis. Cognitive Computation , 1-15.


Workshop Schedule

to be defined

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