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Emotion Detection in Text: A Review - 2018

Emotion Detection In Text: A Review

Survey Paper on Emotion Detection In Text

Research Area:  Machine Learning

Abstract:

In recent years, emotion detection in text has become more popular due to its vast potential applications in marketing, political science, psychology, human-computer interaction, artificial intelligence, etc. Access to a huge amount of textual data, especially opinionated and self-expression text also played a special role to bring attention to this field. In this paper, we review the work that has been done in identifying emotion expressions in text and argue that although many techniques, methodologies, and models have been created to detect emotion in text, there are various reasons that make these methods insufficient. Although, there is an essential need to improve the design and architecture of current systems, factors such as the complexity of human emotions, and the use of implicit and metaphorical language in expressing it, lead us to think that just re-purposing standard methodologies will not be enough to capture these complexities, and it is important to pay attention to the linguistic intricacies of emotion expression.

Keywords:  
Emotion Detection
Text
Machine Learning
Deep Learning

Author(s) Name:  Armin Seyeditabari, Narges Tabari, Wlodek Zadrozny

Journal name:  Computer Science

Conferrence name:  

Publisher name:  arXiv:1806.00674

DOI:  10.48550/arXiv.1806.00674

Volume Information: