The worldwide diffusion of social media has profoundly changed the way we communicate and access information. Social media is changing the way people interact with each other and share information, personal messages, and opinions about situations, objects and past experiences. Increasingly, people interact with each other to share opinions about commercial products on dedicated platforms, report their personal experiences on microblogging and social networking sites, try to solve domain-specific problems through collaborative knowledge building and sharing in online question and answering.
On one hand user-generated content comprise an invaluable wealth of data, ready to be mined for training predictive models. As such, microblogging and online interaction analysis are attracting the interest of researchers and practitioners in NLP, machine learning, big data analysis. Indeed, analysing opinions and emotions conveyed by microposts can yield a competitive advantage for businesses, can serve to gain crucial insights about political sentiment and election results or other social issues.
On the other hand, the pervasive use of online social media in computer-mediated communication, is opening new challenges for social sciences and human-computer studies. Indeed, one of the biggest drawbacks of communication through social media is to appropriately convey and recognize sentiment through text. While display rules for emotions exist and are widely accepted for traditional face-to-face interaction, people might not be prepared for effectively dealing with the barriers of social media to non-verbal communication. As a consequence, the design of systems and mechanisms for fostering emotional awareness in computer-mediated communication is becoming an important technical and social challenge for research in computer-supported collaborative work and social computing.
When talking about sentiment analysis and emotional style of a text, researchers usually refer to a wide range of affective states including emotions, such as joy or fear, moods, opinions, attitudes, as well as continuous dimensions for sentiment characterization, such as valence (positive vs. negative) or intensity (high vs. low). Specifically, the analysis of online user-generated contents presents its own specificities and challenges due to their characteristics, language use, and to the huge available volume of data. Sentiment analysis on such informal texts also poses new challenges due to the presence of slang, misspelled words and micro-blogging features such as hashtags or links and traditional approaches may not be successfully exploited in this domain.
The aims of this symposium include: presenting the state of the art in emotion modelling and tools for online interaction; fostering discussion around interdisciplinary research area at the intersection between cognitive sciences, computational linguistics, and social computing; enhancing the state of the art in affect recognition in social media; discuss challenges and opportunities of research and ethical concerns and applications addressing the role of sentiment and emotions in computer-supported cooperative work and online interaction on social media, with a special focus on education, entertainment, health, e-government, games, hate speech monitoring, etc.
Topics of interest include, but are not limited to, the following:
- Emotion detection in web and social media
- Computational models of affect in social media and online interaction and their validation
- Affect and regulation in computer-mediated interaction
- Sentiment analysis and figurative language in social media contents
- Time evolving opinion and sentiment analysis
- Stance detection in online debates on controversial topics
- Applications of sentiment analysis and emotion detection in social media to education, entertainment, health, e-government, games, hate speech monitoring
- Reusable tools and frameworks
- Ethical issues in affect and opinion detection in user-generated contents
- Affect sensing in online question & answering sites and social computing
Types of Contribution and Guidelines for Submissions
We invite different kinds of submissions to allow researchers to present and discuss studies at different stages of maturity, from early stage research or study design, to full papers reporting empirical studies, theoretical frameworks and their evaluation, experience reports, and so on.
Possible types of contributions include:
- Full papers (6-8 pages) describing emotion modeling and recognition challenges, needs, novel approaches, and frameworks. Empirical evaluation papers are also welcome.
- Short position papers (3-4 pages) describing a new idea or work in progress.
- Posters, data showcase and demo papers (1-2 pages) summarizing a research project, tool, technique or datasets.
Three members from the international program committee will review each submission. Papers will be evaluated based on their originality, relevance to the symposium, and their potential for discussion. The papers with the best reviews will be accepted to be presented and discussed in the workshop.
All papers must conform, at time of submission, to the AISB formatting guidelines (download here the LaTeX Style File or the Word Style File). All submissions must be in English. Papers must be submitted electronically, in PDF format at the following website: https://easychair.org/conferences/?conf=emotionsaisb2018. All accepted papers will distributed to the participants and authors will be invited to present their research at the symposium.
Deadline for submissions:
January 5, 2018 – Now January 19, 2018
Notification of acceptance: February 5, 2018
Final versions to be submitted for inclusion in proceedings: March 5 2018
Symposium date: TBC – During 4th-6th April, 2018
Francesca D’Errico, University of Roma-Tre, Italy
Floriana Grasso, University of Liverpool, UK
Malvina Nissim, University of Groningen, NL
Nicole Novielli, University of Bari, Italy
Viviana Patti, University of Torino, Italy
- Alessandro Ansani, University of Rome 3, Italy
- Ruth Aylett, Heriot-Watt University, UK
- Francesco Barbieri, Pompeu Fabra University, Spain
- Pierpaolo Basile, University of Bari, Italy
- Valerio Basile, Sapienza University, Italy
- Erik Cambria, Nanyang Technological University, Singapore
- Chloé Clavel, Telecom-ParisTech, France
- Mihaela Cocea, University of Portsmouth, UK
- Danilo Croce, Tor Vergata University, Italy
- Rossana Damiano, Università di Torino, Italy
- Celso De Melo, University of Southern California, USA
- Anna Esposito, Seconda Università di Napoli (SUN) and IIASS, Italy
- Valentina Franzoni, University of Perugia, Italy
- Marco Guerini, Fondazione Bruno Kessler (FBK), Italy
- Delia Irazu Hernandez Farias, Universitat Politècnica de València, Spain
- Emiliano Lorini, IRIT, France
- Saif Mohammad, NRC, Canada
- Alessandro Moschitti, Qatar Computing Research Institute, Qatar
- Marinella Paciello, Nettuno University, Italy
- Isabella Poggi, University of Rome 3, Italy
- Paolo Rosso, Universitat Politècnica de València, Spain
- Diana Santos, University of Oslo, Norway
- Björn Schuller, University of Passau, Germany and Imperial College London, UK
- Mohammad Soleymani, University of Geneva, Switzerland
- Khiet Truong, University of Twente, Netherlands
- Carlo Strapparava, Fondazione Bruno Kessler (FBK), Italy
- Enrico Zovato, Nuance Communications, Italy