29.3989, Calls: Applied Ling, Comp Ling, Gen Ling, Psycholing, Socioling/USA

[The LINGUIST List]

LINGUIST List: Vol-29-3989. Mon Oct 15 2018. ISSN: 1069 - 4875.

Subject: 29.3989, Calls: Applied Ling, Comp Ling, Gen Ling, Psycholing, Socioling/USA

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Date: Mon, 15 Oct 2018 01:42:38
From: Niyati Chhaya [nchhaya at adobe.com]
Subject: AAAI Workshop on Affective Content Analysis & Happiness Shared Task: Modeling Affect-in-Action

 
Full Title: AAAI Workshop on Affective Content Analysis & Happiness Shared Task: Modeling Affect-in-Action 
Short Title: AffCon2019 

Date: 27-Jan-2019 - 28-Jan-2019
Location: Honolulu, Hawaii, USA 
Contact Person: Niyati Chhaya
Meeting Email: nchhaya at adobe.com
Web Site: https://sites.google.com/view/affcon2019/home 

Linguistic Field(s): Applied Linguistics; Computational Linguistics; General Linguistics; Psycholinguistics; Sociolinguistics 

Call Deadline: 05-Nov-2018 

Meeting Description:

The theme of the 2nd Affective Content Analysis workshop is “Modeling Affect
in Action.” Affect analysis of content to measure emotions and its experiences
is a multidisciplinary research area with limited cross-disciplinary
collaboration. Other disciplines have adopted psychological models of affect -
Artificial Intelligence (AI), Computational Linguistics (CL) and
Human-computer Interaction (HCI) - 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.


Call for Papers:

The theme of the 2nd Affective Content Analysis workshop is “Modeling Affect
in Action.” Affect analysis of content to measure emotions and its experiences
is a multidisciplinary research area with limited cross-disciplinary
collaboration. Other disciplines have adopted psychological models of affect -
Artificial Intelligence (AI), Computational Linguistics (CL) and
Human-computer Interaction (HCI) - 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.

Invited speakers: Ellen Riloff (University of Utah), Alon Halevy (Megagon
Labs), Marilyn Walker (University of California, Santa Cruz), Lyle Ungar
(University of Pennsylvania)

Call for Shared Task Submissions: CL-AFF: In Pursuit of Happiness
We also invite submissions for the First Shared Task on Computational
Linguistics for Affect Understanding. CL-AFF 2019 comprises two sub-tasks for
analyzing happiness and wellbeing in written language, based on a corpus of
100,000 descriptions of happy moments from HappyDB.

Workshop topics:

We welcome submissions on topics including (but not limited to):

- Machine learning and Deep learning models for affect modeling in content
(image, audio, and video)
- Affect-aware text generation
- Spoken and formal language comparison
- Measurement and evaluation of affective content
- Affective commonsense reasoning
- Affective human-agent, -computer, and-robot interaction
- Multimodal emotion recognition and sentiment analysis
- Psycho-demographic profiling
- Psycho-linguistics, including stylometrics and typography
- Modeling consumer’s affect reactions
- Computational models for consumer behavior theories
- Consumer psychology at scale from big data

Full CFP: https://sites.google.com/view/affcon2019/home
Proceedings of AffCon @ AAAI 2018:
https://aaai.org/Library/Workshops/ws18-01.php
Submission Site:
https://easychair.org/conferences/conference_dir.cgi?a=19604803
 
Important Dates:

October 25, 2018: Abstract Submission (Optional)
November 5, 2018: Submission deadline
November 26, 2018: Notification of acceptance/rejection
November 30, 2018: Early registration deadline
December 5, 2018: Camera-ready versions due
January 27-28, 2019: Workshop at AAAI 2019
 
Co-chairs:

Niyati Chhaya (Adobe Research, nchhaya at adobe.com),
Kokil Jaidka (University of Pennsylvania, kokil.j at gmail.com ),
Lyle Ungar (University of Pennsylvania, ungar at cis.upenn.edu),
Atanu R Sinha (Adobe Research, atr at adobe.com)
Shared Task HappyDB data and labels contributed by Megagon Labs




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