Call for Papers: The 1st Workshop on Computational Affective Science
First Call for Papers: The 1st Workshop on Computational Affective Science (CAS 2026), co-located with the Language Resources and Evaluation Conference (LREC) 2026 in Palma de Mallorca, Spain, May 16.
Website: https://casworkshop.github.io/ https://casworkshop.github.io/
Contact: cas-workshop@googlegroups.com
We invite submissions to the first Workshop on Computational Affective Science (CAS 2026), co-located with LREC 2026, on research related to the understanding of affect and emotions through language and computation. CAS will accept archival long and short paper submissions, featuring substantial, original, and unpublished research. We also encourage submissions of extended abstracts from researchers in the broader Affective Science community, with up to two pages of content featuring the research background/hypotheses and a description of methods/results. Extended abstracts are non-archival, offering the option for publication and presentation at other conference venues.
Motivation
Affect refers to the fundamental neural processes that generate and regulate emotions, moods, and feeling states. Affect and emotions are central to how we organize meaning, to our behavior, to our health and well-being, and to our very survival. Despite this, and even though most of us are intimately familiar with emotions in everyday life, there is much we do not know about how emotions work and how they impact our lives. Affective Science is a broad interdisciplinary field that explores these and related questions about affect and emotions.
Since language is a powerful mechanism of emotion expression, there is a growing use of language data and advanced natural language processing (NLP) algorithms to shed light on fundamental questions about emotions. The Workshop on Computational Affective Science (CAS) aims to be a dedicated venue for work focused specifically on the link between NLP and affective science.
Interdisciplinary Scope
The workshop takes an interdisciplinary approach to affective science and aims at bringing together NLP researchers, scientists, and theorists from many research areas, including psychology, sociology,, neuroscience, and philosophy. Although work in sentiment analysis is decades old, this work often proceeds separately and in different fields from research and theory in affective science. Meanwhile, affective scientists in psychology, sociology, neuroscience and philosophy increasingly seek to use linguistic tools to shed light on the nature of emotions, moods, and feeling states. CAS is therefore co-organized by an interdisciplinary group of researchers (spanning NLP and Affective Science) to foment collaboration at this exciting frontier of research.
Submissions
We invite long and short archival paper submissions, as well as non-archival extended abstracts on a broad range of topics at the intersection of affective science and natural language processing, including but not limited to:
1. The Nature of Affect and Computational Modeling of Emotions
Computational experiments that add to our understanding of affect and emotions, including findings relevant to:
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theories and nature of emotion
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the biology or neuroscience of emotions
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appraisal models
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dimensional models (valence / arousal / dominance)
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models of constructed emotion
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cognitive-affective architectures
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emotion dynamics (emergence, intensification, decay, transitions)
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emotion granularity
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emotion regulation
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affective embodiment
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evolutionary and developmental affect
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emotion–cognition interactions
These areas are relevant not just to human affect, but may also apply to data animals and artificial agents.
2. Affective Data and Resources
Work on compiling and annotating affect-related information in text, speech, facial and bodily expression, and physiological signals (ECG, EEG, GSR, multimodal biosensing), with a focus on text data (monolingual or multilingual) and multimodal data suitable for an NLP venue. Data from underserved languages is especially encouraged.
3. Emotion Recognition, Prediction, and Inference
At the instance level:
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emotion classification (discrete emotions, dimensional ratings)
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emotion intensity estimation
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emotion cause detection
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context-aware affect inference (culture, situation, social setting)
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structured emotion analysis
At the aggregate level:
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creating emotion arcs
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determining broad trends in emotions over time or across locations
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tracking emotional responses toward entities of interest (e.g., climate change)
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document-level and cross-document emotion analysis
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labeling social networks
4. Applications
Including but not limited to:
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Affect and health, psychopathology, and mental disorders
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Affect and behavior/social science (e.g., interpersonal affect, empathy, group-level affect, affect contagion, computational emotion regulation)
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Affect and education
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Affect and literature/narratives/digital humanities
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Affect and commerce
5. Explainability and Interpretability in Computational Affective Models
Work aimed at improving the transparency and interpretability of affective systems. This includes understanding how models represent and infer emotions and identifying key cues driving predictions.
6. Ethics, Fairness, Theory Integration, Philosophical Implications
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Bias and generalizability of affective systems across demographics
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Privacy and ethics in affective data collection
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Examining whether automatic NLP systems rely on current and valid theories of affect and emotion
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The implications of machines modeling or simulating affect
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Societal considerations surrounding affective artificial agents
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Important Dates (tentative):
·Submission deadline:16 Feb 2026
·Notification of acceptance: 16 March 2026
·Camera Ready Paper due: 23 March 2026
·Workshop date: 16 May 2026
Submission Details:
We invite submissions for archival long and short papers, as well as non-archival extended abstracts.
Archival long and short papers should feature novel and unpublished work relating to the topics detailed above.
We also invite submissions of extended abstractsfrom researchers in the broader Affective Science community, with up to two pages of content featuring the research background/hypotheses and a description of methods/results. Extended abstracts are non-archival, offering the option for publication and presentation at other conference venues.
Archival Track:
·Long Paper: Consists of up to 8 pages of content, with additional pages for references, limitations, ethical considerations, and appendices.
·Short Paper: Consists of up to 4 pages of content, with additional pages for references, limitations, ethical considerations, and appendices.
(When preparing camera ready papers, you will be allowed one extra page to address comments by the reviewers.)
Non-Archival Track:
·Extended Abstract: Up to 2 pages.
Submission Format:
All submissions must use the LREC 2026 template and follow the guidelines found at:https://lrec2026.info/authors-kit/ https://lrec2026.info/authors-kit/(Note: extended abstracts can be limited to being 1-2 pages in length).
Mandatory Ethics Section:We ask all authors to include a section on Ethical Considerations in their submission, touching on the ethical concerns and broader societal impacts of the work. This discussion section will not count towards the page limit.
Submission Site:
All submissions must be made through the SoftConf portal. The link to the system will be shared shortly.
Additional Details:
Website: https://casworkshop.github.io/ https://casworkshop.github.io/
Attendance: The workshop will follow the attendance policy of the main conference (https://lrec2026.info/registration-policy/ ).
Organizers:
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Christopher Bagdon, University of Bamberg, Germany
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Krishnapriya Vishnubhotla, National Research Council Canada
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Kristen A. Lindquist, The Ohio State University, USA
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Lyle Ungar, University of Pennsylvania, USA
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Roman Klinger, University of Bamberg, Germany
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Saif M. Mohammad, National Research Council Canada
Contact us at cas-workshop@googlegroups.com with any questions.