Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций
Конференция: International Conference on Digital Transformation and Global Society, DTGS 2021
Год издания: 2022
Идентификатор DOI: 10.1007/978-3-030-93715-7_7
Ключевые слова: classification, emotion analysis, lövheim cube, non-discrete emotion, regression
Аннотация: Nowadays sentiment and emotion analyses are widespread methodologies. However, most of all related tasks in classification manner use discrete classes as target variables: Positive vs Negative (sometimes accompanied by Neutral class), or discrete emotion classes (as Anger, Joy, Fear, etc.). Nonetheless, it is more likely that emotiПоказать полностьюon is not discrete. In this paper, we argue that regression is more natural way to evaluate and predict emotions in text and apply regression framework in study of using Lövheim Cube emotional model for emotion analysis. A regression approach for predicting a point in 3-d space or a configuration of its diagonals can provide us with detailed analytics from an emotional diversity perspective. The preliminary results on regression values prediction performed by five different models demonstrate the need of optimization in regard to a precision. The additional conclusion is that the accuracy of classification is not affected significantly by the target variable type. © 2022, Springer Nature Switzerland AG.
Журнал: Communications in Computer and Information Science
Выпуск журнала: Vol. 1503 CCIS
Номера страниц: 97-107
ISSN журнала: 18650929
Издатель: Springer Science and Business Media Deutschland GmbH