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Related Concept Videos

The Influence of Affect on Cognition01:29

The Influence of Affect on Cognition

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Positive affect significantly influences cognitive processes, including evaluation, memory, creativity, and social judgments. Compared to negative affect, positive emotional states promote more favorable interpretations of stimuli, cognitive flexibility, and heuristic processing. These effects highlight emotions' powerful role in shaping how individuals perceive, remember, and interact with the world.Influence on Evaluation and AttributionWhen individuals experience positive affect, they are...
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Cognition plays a pivotal role in shaping emotional experiences, as demonstrated by Schachter and Singer’s two-factor theory of emotion. According to this model, emotion arises from a combination of physiological arousal and cognitive interpretation. The body’s physiological response to stimuli is ambiguous and only gains emotional significance through cognitive labeling. For instance, an increased heart rate and adrenaline surge while standing near an attractive person may be...
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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...
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Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
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Richard Lazarus' cognitive mediational theory highlights the pivotal role of cognitive appraisal in shaping emotional responses. According to this theory, the evaluation of a stimulus — based on personal values, goals, beliefs, and expectations — mediates the emotional response. This appraisal process is immediate and often occurs unconsciously, influencing the intensity and nature of the resulting emotion.
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Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation
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Towards an intelligent framework for multimodal affective data analysis.

Soujanya Poria1, Erik Cambria2, Amir Hussain1

  • 1School of Natural Sciences, University of Stirling, UK.

Neural Networks : the Official Journal of the International Neural Network Society
|December 20, 2014
PubMed
Summary
This summary is machine-generated.

This study introduces an intelligent agent for multimodal information extraction from social media data. The novel tri-modal approach significantly improves accuracy in analyzing text, audio, and video content.

Keywords:
Affective computingEmotion analysisFacial expressionsMultimodalMultimodal sentiment analysisSpeechText

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Data Science

Background:

  • Social media platforms generate vast amounts of multimodal data daily.
  • Existing methods struggle to effectively process and extract information from diverse data types.

Purpose of the Study:

  • To develop an intelligent agent for effective multimodal information extraction.
  • To infer and aggregate semantic and affective information from user-generated content.

Main Methods:

  • Proposed a novel multimodal information extraction agent.
  • Employed an ensemble feature extraction approach using tri-modal (text, audio, video) features.
  • Utilized the eNTERFACE dataset for preliminary experiments.

Main Results:

  • Achieved an accuracy of 87.95% in multimodal information extraction.
  • Outperformed the best state-of-the-art system by over 10%.
  • Demonstrated a 56% relative reduction in error rate.

Conclusions:

  • The proposed tri-modal approach enhances multimodal information extraction accuracy.
  • The intelligent agent shows significant potential for applications in e-learning, e-health, and human-computer interaction.