CALL FOR PAPERS
Analysis of content to measure affect and its experiences is a growing multidisciplinary research area that still has little cross-disciplinary collaboration. The artificial intelligence (AI) and computational linguistics (CL) communities are making strides in identifying and measuring affect from user signals especially in language, while the human-computer interaction (HCI) community independently explores affect through user experience evaluations. Consumer psychology and marketing pursues a different direction to ground affect in its theoretical underpinnings as well as their real-world applications.

The theme of AffCon 2020 is the study of affect in response to interactive content that may evolve over time. The word ‘affect’ is used to refer to emotion, sentiment, mood, and attitudes including subjective evaluations, opinions, and speculations. Psychological models of affect have been adopted by other disciplines to conceptualize and measure users’ opinions, intentions, and expressions. However, the context-specific characteristics of human affect suggest the need to measure in ways that recognize multiple interpretations of human responses.

We invite papers that offer modeling and measurement of affect and identify the important affect–related dimensions to study consumer behavior. In turn, that allows data models to be more informed in representing behaviors and hence effective in guiding decisions and actions by firms. We welcome submissions on topics including - but not limited to - the following:

-Deep learning-based models for affect modeling in content (image, audio, and video)
-Psycho-demographic profiling
-Affective and Cognitive Content Measurement in Text
-Affect in communication
-Affectively responsive interfaces
-Affective human-agent, -computer, and -robot interaction
-Mirroring affect
-Affect-aware text generation
-Measurement and evaluation of affective content
-Consumer psychology at scale from big data
-Modeling consumer’s affective reactions
-Affect lexica for online marketing communication
-Affective commonsense reasoning
-Multimodal emotion recognition and sentiment analysis
-Computational models for consumer behavior
-Psycho-linguistics, including stylometrics and typography
-Computational linguistics for consumer psychology

We especially invite papers investigating multiple related themes, industry papers, and descriptions of running projects and ongoing work. In the spirit of getting a multidisciplinary community together, we also invite pre-published/in-press work as part of a short presentation and poster session.

Submissions should be made via EasyChair and must follow the formatting guidelines for AAAI-2020 (use the AAAI Author Kit). All submissions must be anonymous and conform to AAAI standards for double-blind review. Both full papers (8 pages including references) and short papers (4 pages including references) that adhere to the 2-column AAAI format will be considered for review.

CALL FOR SHARED TASK SUBMISSIONS: There is a growing interest in understanding how humans initiate and hold conversations. The affective understanding of conversations focuses on the problem of how speakers use affect to react to a situation and to each other. We introduce the OffMyChest Conversation dataset, and invite submissions for the Computational Linguistics Affect Understanding (CL-Aff) Shared Task on Affect in Conversations. Details - https://sites.google.com/view/affcon2020/cl-aff-shared-task

Workshop URL: https://sites.google.com/view/affcon2020
Submission Site: https://easychair.org/conferences/?conf=affcon2020

Important Dates:
November 7, 2019: Abstract Submission (optional) , Submissions via EasyChair
November 15, 2019: Full paper submission
December 04, 2019: Notification of Acceptance/ Rejection
December 13, 2019: AAAI-20 Early registration deadline
December 15, 2019: Camera-ready Versions due
February 7 or 8, 2020: Workshop at AAAI-20


Co-chairs:
Niyati Chhaya (Adobe Research, nchhaya@adobe.com),
Kokil Jaidka (University of Pennsylvania, kokil.j@gmail.com ),
Jennifer Healey (Adobe Research, jehealey@adobe.com),
Lyle Ungar (University of Pennsylvania, ungar@cis.upenn.edu),
Atanu R Sinha (Adobe Research, atr@adobe.com)