We propose a multitask deep neural network for detecting affect-retweet pairs for Twitter tweets. Each task given to our network jointly learns a given affect, e.g. hate, sarcasm etc., along with learning retweeting behaviour as an auxiliary task, from ...

A hard challenge for wearable systems is to measure differences in emotional valence, i.e. positive and negative affect via physiology. However, the stomach or gastric signal is an unexplored modality that could offer new affective information. We ...

Nonverbal vocalizations contain important affective and communicative information, especially for those who do not use traditional speech, including individuals who have autism and are non- or minimally verbal (nv/mv). Although these vocalizations are ...

Empirical evidence suggests that the emotional meaning of facial behavior in isolation is often ambiguous in real-world conditions. While humans complement interpretations of others' faces with additional reasoning about context, automated approaches ...

Students often experience confusion while learning, and if promptly resolved, it can promote engagement and deeper understanding. However, detecting student confusion and intervening in a timely and scalable manner challenges even seasoned instructors. ...

How are strong positive affective states related to eye-tracking features and how can they be used to appropriately enhance well-being in multimedia consumption? In this paper, we propose a robust classification algorithm for predicting strong happy ...

We developed generalizable affect detectors using 133,966 instances of 18 affective states collected from 69,174 students who interacted with an online math learning platform called Algebra Nation over the entire school year. To enable scalability and ...

Current techniques to computationally detect human affect often depend on specialized hardware, work only in laboratory settings, or require substantial individual training. We use sensors in commodity smartphones to estimate affect in the wild with no ...

Affect detection is an important component of computerized learning environments that adapt the interface and materials to students' affect. This paper proposes a plan for developing and testing multimodal affect detectors that generalize across ...

Mind wandering (MW) entails an involuntary shift in attention from task-related thoughts to task-unrelated thoughts, and has been shown to have detrimental effects on performance in a number of contexts. This paper proposes an automated multimodal ...

This paper discusses multimodal affect detection from a fusion of facial expressions and interaction features derived from students' interactions with an educational game in the noisy real-world context of a computer-enabled classroom. Log data of ...

Physiological signals provide valuable information about human physical and mental states. For decades, sophisticated equipment has been used to measure them in health and psychological applications. More recently a variety of low-cost portable ...

Affect detection is a key component in developing intelligent educational interfaces that are capable of responding to the affective needs of students. In this paper, computer vision and machine learning techniques were used to detect students' affect ...

The well-studied Baker et al., affect detectors on boredom, frustration, confusion and engagement concentration with ASSISTments dataset were used to predict state tests scores, college enrollment, and even whether a student majored in a STEM field. In ...

Choosing a college major is a major life decision. Interests stemming from students' ability and self-efficacy contribute to eventual college major choice. In this paper, we consider the role played by student learning, affect and engagement during ...

This research predicted behavioral disengagement using quitting behaviors while learning from instructional texts. Supervised machine learning algorithms were used to predict if students would quit an upcoming text by analyzing reading behaviors ...

Recently, there has been considerable interest in understanding the relationship between student affect and cognition. This research is facilitated by the advent of automated sensor-free detectors that have been designed to "infer" affect from the logs ...

We have developed an intelligent agent to engage with users in virtual drama improvisation previously. The agent was able to perform sentence-level affect detection especially from inputs with strong emotional indicators. In this research, we employ ...

It is hypothesized that the ability for a system to automatically detect and respond to users' affective states can greatly enhance the human-computer interaction experience. Although there are currently many options for affect detection, keystroke ...

Sentiment analysis is a growing field of research, driven by both commercial applications and academic interest. In this paper, we explore multiclass classification of diary-like blog posts for the sentiment dimensions of valence and arousal, where the ...