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Valence is an inferred criterion from instinctively generated emotions; it is the property specifying whether feelings/affects are positive, negative or neutral. [2] The existence of at least temporarily unspecified valence is an issue for psychological researchers who reject the existence of neutral emotions (e.g. surprise , sublimation). [ 2 ]
For example, a positive valence would shift the emotion up the top vector and a negative valence would shift the emotion down the bottom vector. [11] In this model, high arousal states are differentiated by their valence, whereas low arousal states are more neutral and are represented near the meeting point of the vectors.
Affect, in psychology, is the underlying experience of feeling, emotion, attachment, or mood. [1] It encompasses a wide range of emotional states and can be positive ...
For example, not everyone furrows their brow when they are feeling angry. Moreover, these emotional symbols are not universal due to cultural differences. For example, when Western individuals are asked to identify an emotional expression on a specific face, in an experimental task, they focus on the target's facial expression.
A common way in which emotions are conceptualized in sociology is in terms of the multidimensional characteristics including cultural or emotional labels (for example, anger, pride, fear, happiness), physiological changes (for example, increased perspiration, changes in pulse rate), expressive facial and body movements (for example, smiling ...
For example, children may understand that upon receiving a gift they should display a smile, irrespective of their actual feelings about the gift. [79] During childhood, there is also a trend towards the use of more cognitive emotion regulation strategies, taking the place of more basic distraction, approach, and avoidance tactics.
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Decades of scientific research have been conducted developing and evaluating methods for automated emotion recognition. There is now an extensive literature proposing and evaluating hundreds of different kinds of methods, leveraging techniques from multiple areas, such as signal processing, machine learning, computer vision, and speech processing.