Human emotions have deep evolutionary roots, a fact that may explain their complexity and provide tools for clinical practice

By R. Plutchik. 2016

982 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Emotionally-Aware Chatbots: A Survey (2019, background): “Emolex contains 14.182 words associated with eight primary emotion based on [40] : joy, sadness, anger, fear, trust, surprise, disgust, and anticipation.”
EmoNet: Fine-Grained Emotion Detection with Gated Recurrent Neural Networks (2017, background): “Plutchik (Plutchik, 2001) organizes emotions in a three-dimensional circumplex model analogous to the colors on a color wheel.”
CARER: Contextualized Affect Representations for Emotion Recognition (2018, background): “In emotion recognition studies, Plutchik’s wheel of emotions (Plutchik, 2001) or Ekman’s six basic emotions (Ekman, 1992), are commonly adopted to de-ﬁne emotion categories (Mohammad, 2012; Sut-tles and Ide, 2013).”
Sentiment Analysis: Detecting Valence, Emotions, and Other Affectual States from Text (2016, methodology): “Below we summarize work on compiling textual datasets labeled with emotions and automatic methods for detecting emotions in text.”
Survey on Emotional Body Gesture Recognition (2018, unknown): “Categorical (a) (here a universal set of emotions as define by Ekman [46]), (b) dimensional (Russell’s model depicted) [47], and (c) componential models (Plutchik’s model shown) [48].”