A Survey on Sentiment and Emotion Analysis for Computational Literary Studies

Ethnic minorities' mentality and homosexuality psychology in literature: A text emotion analysis with NRC lexicon

“…However, there is still much to do for the emotion analysis method combined with the literature study. Though nowadays, researchers have paid more attention to Digital Humanities (DH), turning into a computational turn in which studies try to track plot developments and textual emotions [21]. Based on existing research, this paper aims to not only determine if existing lexica are suitable for detecting characters' emotions and how they fluctuate with changes in the storyline but also to evaluate the effectiveness of conventional emotion analysis methods in providing a proper display of the ups and downs of the plot.…”

Affective cyborgs and other artificial constructs in feminist science fiction: Sideshow and Six Moon Dance by Sheri Tepper

“…He argues that emotions have adaptive purposes, and has later developed an emotion classification, criticised, but still in use today (Plutschik's wheel of emotions: joy vs sorrow, anger versus fear, trust versus disgust, and surprise versus anticipation, 2001; cf. Ekman's theory of basic emotions and Russel's circumplex model of affect, Kim & Klinger, 2019). Computer scientists Leysia Palen and Susanne Bødker provide a summary of how emotion has become an important issue in human-computer interaction and the diverse approaches in their field, claiming that emotion is so large an idea that it can be descriptive of all kinds of interaction and non-interaction, meaning that it is fundamental to these things, and so therefore it is not powerful to us as analysts of human computer interaction.…”

Emotion-Aware, Emotion-Agnostic, or Automatic: Corpus Creation Strategies to Obtain Cognitive Event Appraisal Annotations

“…There is a wealth of literature in psychology surrounding emotions, specifically regarding the way they are elicited, their universal validity, their number and stereotypical expressions, and their function (Scherer, 2000;Gendron and Feldman Barrett, 2009). The two prominent traditions which have dominated the field of emotion classification in natural language processing are discrete and dimen-sional models (Kim and Klinger, 2019).…”