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AAAI 2019 Workshop Call for Paper

  • 1.  AAAI 2019 Workshop Call for Paper

    Posted 09-24-2018 13:34

    Posted by: Atanu R Sinha, Adobe Research,  atr@adobe.com

     

     

    AFFCON 2019: AAAI WORKSHOP ON  AFFECTIVE CONTENT ANALYSIS

     

    CALL FOR PAPERS

     

    The role of affect in consumer behavior is well studied in literatures across Consumer Psychology and Marketing Science. Big Data have made available data on self-expressions across many platforms, generating increased interest in studying affect, most of which earlier could at best be studied only in experimental settings. Yet, analysis of affect has severely lagged behind in at least two ways: (i) lack of advances in its measurement relative to easy access to data from which to measure affect; and (ii) significant underrepresentation in quantitative models of user behavior relative to affect's perceived importance. This is an important omission because such models use what can be measured and if not measured important effects get ignored, resulting in poor decision models. In turn, this leads to poorly-informed marketer actions, such as, predictions and recommendations. In short, although the role of affect is widely recognized, its use in computational models is stymied by rudimentary measurement which does not capture nuances. The computational linguists are bringing knowledge and tools from Natural Language Processing and Machine Learning to address this problem. The other half can come from understanding of consumer behavior, where Consumer Psychologists and Marketing Scientists can play a crucial part. This workshop is the second of its kind to bring together intellectual leadership from these two communities in a single forum to cross-pollinate research toward comprehensive analysis of affect from Big Data. Held alongside the major AI conference gives the workshop the prominence and voice to promote more research in the confluence of Consumer Psychology, Marketing Science, AI, Computational Linguistics, and Human-Computer Interaction.

     

    Centered around the theme of "Modeling Affect in Action," this 2nd Affective Content Analysis Workshop welcomes submissions on topics including (but not limited to):

     

    ●      Modeling consumer's affective reactions from Big data

    ●      Computational models for consumer behavior theories

    ●      Consumer psychology at scale from big data

    ●      Inclusion of Affect in Automated Consumer Choice Models for Big data

    ●      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

    ●      Machine learning and Deep learning models for affect modeling in content (image, audio, and video)

     

    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 a part of a short presentation and poster session.

     

    Invited speakers: Alon Halevy (Megagon Labs), Ellen Riloff (University of Utah), Lyle Ungar (University of Pennsylvania).

     

    Check out the proceedings of the 1st Affective Content Analysis Workshop AffCon@AAAI 2018 at  https://aaai.org/Library/Workshops/ws18-01.php

    Workshop URL: https://sites.google.com/view/affcon2019/home

     

    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@adobe.com),

    Kokil Jaidka (University of Pennsylvania, kokil.j@gmail.com ),

    Lyle Ungar (University of Pennsylvania, ungar@cis.upenn.edu),

    Atanu R Sinha (Adobe Research, atr@adobe.com)