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X-SENTIMENT 2021 : X-SENTIMENT@ESWC 6th International Workshop on eXplainable SENTIment Mining and EmotioN deTection | |||||||||||||||
| Link: https://danilo-dessi.github.io/xsentiment/ | |||||||||||||||
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Call For Papers | |||||||||||||||
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Call for Papers
Sixth International Workshop on eXplainable SENTIment Mining and EmotioN deTection held as a part of ESWC 2021. Workshop: June 7th, 2021 - Hersonissos, Greece or Online https://danilo-dessi.github.io/xsentiment/ ----------------------------------------------------- Important Dates ----------------------------------------------------- Submissions: March 14th, 2021 Notifications: March 31st, 2021 Camera-Ready Contributions: April 9th, 2021 Final papers zip archive: April 16th, 2021 Workshop date: 8th, 2021 All deadlines are 11:59pm, AoE time (Anywhere on Earth). ------------------------------------------------------ Workshop Aims and Scope ------------------------------------------------------ As the Web rapidly evolves, people are becoming increasingly enthusiastic about interacting, sharing, and collaborating through social networks, online communities, blogs, wikis. Therefore, it is critical to correctly interpret sentiments and opinions expressed or reported about social events, political movements, company strategies, marketing campaigns, and any other form or online interaction. Models driven by sub-symbolic Artificial Intelligence such as machine learning algorithms and vector representations have achieved state-of-the-art results for Sentiment Analysis tasks. Sub-symbolic AI models get very accurate results but with a limited understanding of patterns and features used to correctly classify into sentiment categories. Thus, these models lack transparency, traceability, and explainability on how the decisions are taken. This limits Artificial Intelligence methods to produce human-comprehensible solutions, reducing the trust towards the machine generated results. Within this scenario, semantic technologies with explicit semantics can be leveraged to explain why a resource has been classified in a specific sentiment category, inducing trustworthiness and avoiding biases. -------------------------------------------------------- Workshop Keywords -------------------------------------------------------- Sentiment Analysis - Deep Learning - Knowledge Graph - Explainability ------------------------------------------------------- Workshop Topics ------------------------------------------------------- We are interested in novel contributions to explain Sentiment Analysis results through the use and development of methodologies based on semantics, focused but not limited to the following areas: Methodologies: - Methods to build ontologies for Sentiment Analysis. - Methods to build knowledge graphs for Sentiment Analysis. - Methods to build lexicons for Sentiment Analysis. - Explainable Machine Learning models for Sentiment Analysis. - Bias detection through semantics for Sentiment Analysis. - Semantics for toxicity and hate speech detection. - Application of existing semantic technologies multimedia data. - Multilingual Sentiment Analysis methodologies. Representation Methods: - Ontologies for Sentiment Analysis. - Knowledge graphs for Sentiment Analysis. - Combination of existing resources (e.g., SenticNet) with embedding representations. - Novel Word Embeddings for Sentiment Analysis. - Knowledge Graph Embeddings for Sentiment Analysis. - Reviews about existing limitations. Case Study Exploration: - Educational environments. - Healthcare systems. - Scholarly discussions (e.g., peer review process discussions, mailing lists, etc.). - Mental health systems. - News platforms. - Social networks. ------------------------------------------------------- Submission Details ------------------------------------------------------- The submissions must be in English and adhere to the CEUR-WS one-column template. The papers should be submitted as PDF files to OpenReview. The review process will be single-blind. Please be aware that at least one author per paper must be registered and attend the workshop to present the work. We will consider three different submission types: - Full Papers (10-12 pages) should be clearly placed with respect to the state of the art and state the contribution of the proposal in the domain of application, even if presenting preliminary results. In particular, research papers should describe the methodology in detail, experiments should be repeatable, and a comparison with the existing approaches in the literature is encouraged. - Short Papers (5-9 pages) should describe significant novel work in progress. Compared to full papers, their contribution may be narrower in scope, be applied to a narrower set of application domains, or have weaker empirical support than that expected for a full paper. Submissions likely to generate discussions in new and emerging areas of sentiment explainability are encouraged. - Position Papers (2-4 pages) should introduce new point of views in the workshop topics or summarize the experience of a group in the field. Submissions should not exceed the indicated number of pages, including any diagrams and references. Each submission will be reviewed by three independent reviewers on the basis of relevance for the workshop, novelty/originality, significance, technical quality and correctness, quality and clarity of presentation, quality of references and reproducibility. The accepted papers and the material generated during the meeting will be available on the workshop website. The workshop proceedings will be sent for inclusion in a CEUR-WS volume and consequently indexed on Google Scholar, DBLP, and Scopus. The best paper may be included in the supplementary proceedings of ESWC 2021, which will appear in the Springer LNCS series. ---------------------------------------------------------- Attending ---------------------------------------------------------- TBD --------------------------------------------------------- Workshop Chairs --------------------------------------------------------- Davide Buscaldi https://sites.google.com/site/davidebuscaldi/ Laboratoire d'Informatique de Paris Nord (LIPN) Université Sorbonne Paris Nord Email: davide.buscaldi@lipn.univ-paris13.fr Danilo Dessì https://www.fiz-karlsruhe.de/en/forschung/lebenslauf-und-publikationen-dr-danilo-dessi Information Service Engineering FIZ- Karlsruhe Leibniz Institute for Information Infrastructure Karlsruhe Institute of Technology (KIT) - Institute AIFB Email: danilo.dessi@fiz-karlsruhe.de Mauro Dragoni https://pdi.fbk.eu/people/profile/dragoni Process & Data Intelligence - Fondazione Bruno Kessler University of Trento Email: dragoni@fbk.eu Diego Reforgiato Recupero https://people.unica.it/diegoreforgiato/en/ Department of Mathematics and Computer Science University of Cagliari Email: diego.reforgiato@unica.it Harald Sack https://www.fiz-karlsruhe.de/en/forschung/lebenslauf-prof-dr-harald-sack Information Service Engineering FIZ- Karlsruhe Leibniz Institute for Information Infrastructure Karlsruhe Institute of Technology (KIT) - Institute AIFB Email: harald.sack@fiz-karlsruhe.de ----------------------------------------------------------- Contacts ----------------------------------------------------------- For general enquiries on the workshop, please send an email to danilo.dessi@fiz-karlsruhe.de |
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