Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Labeling Emotion

Labeling Emotion

Emotional labeling is a cognitive process that involves identifying and naming one's emotions, such as anger, fear, happiness, or sadness. It allows individuals to recognize and express their internal emotional states, a critical aspect of emotional regulation and communication. Labeling emotions requires more than mere recognition; it also involves drawing upon memory and contextual cues to understand the current situation and apply a corresponding emotional label. For instance, feeling...

Cognitive Theories: Schachter-Singer Theory of Emotion

Cognitive Theories: Schachter-Singer Theory of Emotion

Stanley Schachter and Jerome Singer proposed the two-factor theory of emotion, which emphasizes the interplay between physiological arousal and cognitive labeling in forming emotional experiences. This theory suggests that emotions are not simply a result of physiological responses but rather a combination of these responses and the individual's cognitive interpretation of them.
Physiological Arousal and Cognitive Labeling
According to this theory, when an individual experiences physiological...

Physiology of Emotion

Physiology of Emotion

The physiology of emotions is a multifaceted process involving the autonomic nervous system, brain structures, hormones, and neurotransmitters. This intricate interplay dictates how emotions manifest in the body and influence behavior.
Autonomic Nervous System
The autonomic nervous system (ANS) plays a critical role in emotional responses by regulating involuntary physiological functions. It consists of two main components: the sympathetic and parasympathetic systems. The sympathetic system...

Empathy

Empathy

Some researchers suggest that altruism operates on empathy. Empathy is the capacity to understand another person’s perspective, to feel what he or she feels. An empathetic person makes an emotional connection with others and feels compelled to help (Batson, 1991). Empathy can be expressed in several ways, including cognitive, affective, and motor.

Facial Feedback Hypothesis

Facial Feedback Hypothesis

Charles Darwin proposed that facial expressions are an evolutionary adaptation for communication. He argued that these expressions are not influenced by culture but are universal across species. For example, a snarling expression with exposed teeth signals a threat in many animals, including humans. Darwin also suggested that displaying an emotion can intensify the feeling. Smiling, for example, could enhance one's sense of happiness. This idea laid the foundation for understanding the role of...

Emotional Expression

Emotional Expression

Emotional expression encompasses how individuals convey their emotions through verbal communication and non-verbal cues. These non-verbal actions include facial expressions, body language, and physical gestures, such as frowning or smiling. Among these, facial expressions play a crucial role in emotional expression and are understood universally, indicating a biological basis for how humans communicate emotions.
Universal Facial Expressions
Psychologist Paul Ekman identified seven basic...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Recognizing the Known Unknowns; the Interaction Between Reflective Thinking and Optimism for Uncertainty Among Software Developer's Security Perceptions.

Technology, mind, and behavior·2026

Same author

"<i>Are we in this together?</i>": embedding social identity detection in drones improves emergency coordination.

Frontiers in psychology·2023

Same author

Digital Intervention in Loneliness in Older Adults: Qualitative Analysis of User Studies.

JMIR formative research·2023

Same author

Significant Features for Human Activity Recognition Using Tri-Axial Accelerometers.

Sensors (Basel, Switzerland)·2022

Same author

Designing Tangibles to Support Emotion Logging for Older Adults: Development and Usability Study.

JMIR human factors·2022

Same author

Public opinion of the Irish "COVID Tracker" digital contact tracing App: A national survey.

Digital health·2022

Search research articles

Related Experiment Videos

A hybrid model for automatic emotion recognition in suicide notes.

Hui Yang¹, Alistair Willis, Anne de Roeck

¹Department of Computing, Open University, Milton Keynes, United Kingdom.

Biomedical Informatics Insights

|August 11, 2012

Summary

Researchers developed an automated system for identifying emotions in suicide notes, achieving first place in a medical natural language processing challenge. This system demonstrates the potential of machine learning for affective text analysis with sufficient annotated data.

Keywords:

emotion recognition hybrid model keyword-based model machine-learning-based model result integration

Related Experiment Videos

Area of Science:

Computational linguistics
Affective computing
Medical informatics

Background:

The 2011 i2b2/VA/Cincinnati challenge focused on automatic sentiment analysis in suicide notes.
Identifying specific emotions at the sentence level from clinical text is a complex task.

Purpose of the Study:

To develop and evaluate an automated system for recognizing 15 specific emotions in suicide notes.
To participate and rank in the Track 2 Shared Task of the 2011 i2b2/VA/Cincinnati Medical Natural Language Processing Challenge.

Main Methods:

A hybrid approach combining lexicon-based keyword spotting, Conditional Random Fields (CRF) for emotion cue identification, and machine learning for classification.
Integration of results from different techniques using vote-based merging strategies.

Main Results:

The system achieved a micro-averaged F-measure score of 61.39% for textual emotion recognition.
The automated system ranked 1st among 24 participating teams, outperforming the manually-annotated gold standard.

Conclusions:

Effective automated emotion recognition from suicide notes is feasible with a large annotated corpus.
The proposed hybrid model demonstrates strong performance in identifying affective text in a challenging clinical domain.