NEWS:

Date & Time: January 27, 2019 at 9am

Venue: Kahili 1 (Level 6 of the Kalia Conference Center, The Hilton)

• The proceedings - http://ceur-ws.org/Vol-2328/
• Camera ready versions of the paper available here
• The schedule is up!
• We're sold out! But you could try to register on the spot on Jan 27
• Registration for AAAI 2019 is at - https://aaai.org/Conferences/AAAI-19/registration/
• Workshop posterboards are 30"x40". We recommend portrait landscape, but you can display the posters as you'd like.

Introduction

Affect analysis refers to the set of techniques which identify and measure the ‘experience of an emotion’. This interdisciplinary workshop focuses on analyzing affect in content including text, audio, images, and videos. The word ‘affective’ is used to refer to emotion, sentiment, personality, mood, and attitudes including subjective evaluations, opinions, and speculations. All methods and models that measure affective responses to content are in the scope of the workshop. We encourage interdisciplinary participation and cross-disciplinary approaches from computational linguistics (CL), consumer psychology, human-computer interaction (HCI), marketing science and cognitive science, among others.

The theme of the 2nd Affective Content Analysis workshop is "Modeling Affect-in-Action" and we're announcing a Shared Task (see CL-Aff Shared Task CFP) to encourage the development of new models and approaches for modeling happy moments. This Shared Task is based on the HappyDB corpus.

Models of affect have recently been adapted for user-generated content. However, the exponentially increasing size and the dynamic, multimedia nature of this data make it difficult to detect and measure affect. Furthermore, the subjective nature of human affect suggests the need to measure in ways that recognize multiple interpretations of human responses. A few key challenges are:

• Standardizing the measurement of affect in order to meaningfully compare different affective models against each other
• Addressing the challenges in cross-media, cross-domain and cross-platform affect analysis
• Identifying consumer psychology theories and behaviors related to affect, which are amenable to computational modeling

The AI community is well-poised to propose new solutions, approaches and frameworks to tackle these and other challenges. This workshop invites papers that address these and other topics, propose novel solutions for well-established problems, offer modeling and measurement of affect, and identify the best affect–related dimensions to study consumer behavior. Potential examples include deep learning for affect analysis, leveraging traditional affective computing algorithms (that are built on multi–modal data and sensors) for text and so on.

Another area of focus for this workshop is the need of standardized baselines, datasets, and evaluation metrics. Papers describing novel language resources, evaluation metrics and standards for affect analysis and understanding are also encouraged.