36.3851, Confs: 1st Workshop on Computational Affective Science at LREC 2026 (Spain)

Tue Dec 16 15:05:02 UTC 2025

LINGUIST List: Vol-36-3851. Tue Dec 16 2025. ISSN: 1069 - 4875.

Subject: 36.3851, Confs: 1st Workshop on Computational Affective Science at LREC 2026 (Spain)

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Date: 15-Dec-2025
From: Krishnapriya Vishnubhotla [vkpriya at cs.toronto.edu]
Subject: 1st Workshop on Computational Affective Science at LREC 2026

1st Workshop on Computational Affective Science at LREC 2026
Short Title: CAS 2026
Theme: Bridging NLP and Affective Science to study the nature of
affect and emotion

Date: 11-May-2026 - 16-May-2026
Location: Mallorca, Spain
Contact: CAS Workshop 2026
Contact Email: workshop.cas1 at gmail.com
Meeting URL: https://casworkshop.github.io/

Linguistic Field(s): Applied Linguistics; Computational Linguistics;
Sociolinguistics; Text/Corpus Linguistics

Submission Deadline: 16-Feb-2026

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submissions, featuring substantial, original, and unpublished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:
 - theories and nature of emotion
 - the biology or neuroscience of emotions
 - appraisal models
 - dimensional models (valence / arousal / dominance)
 - models of constructed emotion
 - cognitive-affective architectures
 - emotion dynamics (emergence, intensification, decay, transitions)
 - emotion granularity
 - emotion regulation
 - affective embodiment
 - evolutionary and developmental affect
 - 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:
 - emotion classification (discrete emotions, dimensional ratings)
 - emotion intensity estimation
 - emotion cause detection
 - context-aware affect inference (culture, situation, social setting)
 - structured emotion analysis
At the aggregate level:
 - creating emotion arcs
 - determining broad trends in emotions over time or across locations
 - tracking emotional responses toward entities of interest (e.g.,
climate change)
 - document-level and cross-document emotion analysis
 - labeling social networks
4. Applications
Including but not limited to:
 - Affect and health, psychopathology, and mental disorders
 - Affect and behavior/social science (e.g., interpersonal affect,
empathy, group-level affect, affect contagion, computational emotion
regulation)
 - Affect and education
 - Affect and literature/narratives/digital humanities
 - 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
 - Bias and generalizability of affective systems across demographics
 - Privacy and ethics in affective data collection
 - Examining whether automatic NLP systems rely on current and valid
theories of affect and emotion
 - The implications of machines modeling or simulating affect
 - Societal considerations surrounding affective artificial agents
Important Dates (tentative):
Submission deadline:16  Feb 2026
Notification of acceptance: 16 March 2026
Camera Ready Paper due: 30 March 2026
Workshop date: TBA (11-16 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 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.
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/ (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/
Attendance: The workshop will follow the attendance policy of the main
conference (https://lrec2026.info/registration-policy/ ).
Organizers:
Christopher Bagdon, University of Bamberg, Germany
Krishnapriya Vishnubhotla, National Research Council Canada
Kristen A. Lindquist, The Ohio State University, USA
Lyle Ungar, University of Pennsylvania, USA
Roman Klinger,  University of Bamberg, Germany
Saif M. Mohammad, National Research Council Canada
Contact us at workshop.cas1 at gmail.com with any questions.

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