This full-day workshop will start with a keynote followed by regular research paper presentations for all four sessions. There will also be a poster session and CL-Aff Shared Task session. We will end the workshop with a fishbowl-style discussion among the organizers, keynote speakers and the participants to decide on further directions and enhancements to the workshop.

Session 1

• 0830-0900 : Poster session 1 Setup
• 0900 - 0915 : Welcome
• 0915 - 1000 : Invited Speaker: Louis-Philippe Morency , Multimodal AI: Understanding Human Communication Dynamics.
• 1000- 1015 : Context-Dependent Models for Predicting and Characterizing Facial Expressiveness. Victoria Lin, Jeffrey Girard, & Louis-Philippe Morency.
• 1015- 1030 : Poster Session 1 fastforwards

1030 - 1100 : Coffee Break & Poster Session 1

Session 2

• 1100 - 1145 : Invited speaker: Daniel McDuff, Building Intelligent & Visceral Machines.
• 1145 - 1200 : Bidirectional Dilated LSTM with Attention for Fine-grained Emotion Classification in Tweets. Annika Marie Schoene, Alexander P Turner, & Nina Dethlefs.
• 1200 - 1230: Invited speaker: Natasha Jaques, Reinforcement learning from Affective Cues in Dialogue.

1230 - 1400 : Lunch (on your own)

1330 - 1400 : Poster Session 2 Setup

Session 3

• 1400 - 1445 : Invited speakers: Donna Hoffman, & Tom Novak, Reifying the Possibility Space of IoT Automation Practices: A Machine Learning Approach.
• 1445 - 1500 : Invited paper: Alain Lemaire and O. Netzer, Review Based Recommendation - The Role of Linguistic Match between Users
• 1500 - 1508: CLAff Best paper 1: BERT-based Ensembles for Modeling Disclosure and Support in Conversational Social Media Text . Kartikey Pant, Tanvi Dadu & Radhika Mamidi.
• 1509 - 1516: CL-Aff Best paper 2: Detecting Disclosure and Support via Deep Multi-Task Learning. Weizhao Xin, & Diana Inkpen
• 1517 - 1530 : CL-Aff Poster Fast Forwards

1530 - 1600 : Coffee Break and Poster Session 2 (CL-Aff Shared Task)

Session 4

• 1600 - 1645 : Invited speaker: Robert Kraut. Using Big Data to Understand and Improve Online Support Groups
• 1645 - 1700 : A Hierarchical Approach to Machine Emotional Intelligence. Hortense Fong, & Vineet Kumar.
• 1700 - 1730: Panel discussion

• Poster Session 1 (On display in the room and presented between 10.30 am - 11.00 am and 12.30 pm - 1.15 pm)
  • A Siamese Neural Network with Modified Distance Loss For Transfer Learning in Speech Emotion Recognition. Kexin Feng, & Theodora Chaspari.
  • Attentive RNNs for Continuous-time Emotion Prediction in Music Clips. Sanga Chaki, Pranjal Doshi, Priyadarshi Patnaik, & Sourangshu Bhattacharya.
  • Automatically Identifying Customer Needs with Attribute Sentiment Model. Jiaming Xu, Bo Tang, Xiao Liu, & Feiyu Xiong.
  • A Deep Learning Approach Towards Multimodal Stress Detection. Cristian Paul Bara, Michalis Papakostas, & Rada Mihalcea.
  • Complementary Fusion of Multi-Features and Multi-Modalities in Sentiment Analysis. Feiyang Chen, Ziqian Luo, Yanyan Xu, & Dengfeng Ke.

• Poster Session 2 (CL-Aff Shared Task) (On display after 1.15pm and presented between 3.00 pm - 4.00 pm)
  • Semi-supervised Models via Data Augmentation for Classifying Interactive Affective Responses. Jiaao Chen, Yuwei Wu, & Diyi Yang
  • Detecting Disclosure and Support via Deep Multi-Task Learning. Weizhao Xin, & Diana Inkpen
  • Multi-modal Sentiment Analysis using Super Characters Method on Low-power CNN Accelerator Device. Baohua Sun, Lin Yang, Hao Sha, & Michael Lin .
  • A Text Classification Using Fine-Tuned Word and Emotion Embedding. Jiwung Hyun, Byung-Chull Bae, &Yun-Gyung Cheong.
  • Modeling Supportiveness and Disclosure in Conversational Social Media Text. Kartikey Pant, Tanvi Dadu & Radhika Mamidi.
  • Contextual representation of self-disclosure and supportiveness in short text. Chandan Akiti, Sarah Rajtmajer, & Anna Squicciarini.