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Found 15 papers, 1 papers with code
Inferring Social Media Users' Mental Health Status from Multimodal Information
In this paper, we explore the use of multimodal cues present in social media posts to predict users{'} mental health status.
What Makes a Good Counselor? Learning to Distinguish between High-quality and Low-quality Counseling Conversations
Our results suggest important language differences in low- and high-quality counseling, which we further use to derive linguistic features able to capture the differences between the two groups.
Towards Multimodal Sarcasm Detection (An \_Obviously\_ Perfect Paper)
As a first step towards enabling the development of multimodal approaches for sarcasm detection, we propose a new sarcasm dataset, Multimodal Sarcasm Detection Dataset (MUStARD), compiled from popular TV shows.
Box of Lies: Multimodal Deception Detection in Dialogues
Deception often takes place during everyday conversations, yet conversational dialogues remain largely unexplored by current work on automatic deception detection.
Identity Deception Detection
This paper addresses the task of detecting identity deception in language.
Understanding and Predicting Empathic Behavior in Counseling Therapy
Counselor empathy is associated with better outcomes in psychology and behavioral counseling.
Predicting Counselor Behaviors in Motivational Interviewing Encounters
As the number of people receiving psycho-therapeutic treatment increases, the automatic evaluation of counseling practice arises as an important challenge in the clinical domain.
A Multimodal Dataset for Deception Detection
This paper presents the construction of a multimodal dataset for deception detection, including physiological, thermal, and visual responses of human subjects under three deceptive scenarios.
Learning Sentiment Lexicons in Spanish
In this paper we present a framework to derive sentiment lexicons in a target language by using manually or automatically annotated data available in an electronic resource rich language, such as English.
