Article

Towards Text-based Emotion Detection—A Survey and Possible Improvements

Authors:

Edward Chao-Chun Kao,

Chun-Chieh Liu,

Ting-Hao Yang,

Chang-Tai Hsieh,

Von-Wun SooAuthors Info & Claims

ICIME '09: Proceedings of the 2009 International Conference on Information Management and Engineering

Pages 70 - 74

https://doi.org/10.1109/ICIME.2009.113

Published: 03 April 2009 Publication History

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Abstract

This paper presents an overview of the emerging field of emotion detection from text and describes the current generation of detection methods that are usually divided into the following three main categories: keyword-based, learning-based, and hybrid recommendation approaches. Limitations of current detection methods are examined, and possible solutions are suggested to improve emotion detection capabilities in practical systems, which emphasize on human-computer interactions. These solutions include extracting keywords with semantic analysis, and ontology design with emotion theory of appraisal. Furthermore, a case-based reasoning architecture is proposed to combine these solutions.

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Polignano MBasile Pde Gemmis MSemeraro GPapadopoulos GSamaras GWeibelzahl SJannach DSantos O(2019)A Comparison of Word-Embeddings in Emotion Detection from Text using BiLSTM, CNN and Self-AttentionAdjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization10.1145/3314183.3324983(63-68)Online publication date: 6-Jun-2019
https://dl.acm.org/doi/10.1145/3314183.3324983
Lombardo GFornacciari PMordonini MSani LTomaiuolo M(2019)A combined approach for the analysis of support groups on Facebook - the case of patients of hidradenitis suppurativaMultimedia Tools and Applications10.1007/s11042-018-6512-578:3(3321-3339)Online publication date: 1-Feb-2019
https://dl.acm.org/doi/10.1007/s11042-018-6512-5
Samonte MPunzalan HSantiago RLinchangco PBen-Othman JGang FLiu JArai M(2017)Emotion detection in blog posts using keyword spotting and semantic analysisProceedings of the 3rd International Conference on Communication and Information Processing10.1145/3162957.3162963(6-13)Online publication date: 24-Nov-2017
https://dl.acm.org/doi/10.1145/3162957.3162963
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ICIME '09: Proceedings of the 2009 International Conference on Information Management and Engineering

April 2009

725 pages

ISBN:9780769535951

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IEEE Computer Society

United States

Publication History

Published: 03 April 2009

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Polignano MBasile Pde Gemmis MSemeraro GPapadopoulos GSamaras GWeibelzahl SJannach DSantos O(2019)A Comparison of Word-Embeddings in Emotion Detection from Text using BiLSTM, CNN and Self-AttentionAdjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization10.1145/3314183.3324983(63-68)Online publication date: 6-Jun-2019
https://dl.acm.org/doi/10.1145/3314183.3324983
Lombardo GFornacciari PMordonini MSani LTomaiuolo M(2019)A combined approach for the analysis of support groups on Facebook - the case of patients of hidradenitis suppurativaMultimedia Tools and Applications10.1007/s11042-018-6512-578:3(3321-3339)Online publication date: 1-Feb-2019
https://dl.acm.org/doi/10.1007/s11042-018-6512-5
Samonte MPunzalan HSantiago RLinchangco PBen-Othman JGang FLiu JArai M(2017)Emotion detection in blog posts using keyword spotting and semantic analysisProceedings of the 3rd International Conference on Communication and Information Processing10.1145/3162957.3162963(6-13)Online publication date: 24-Nov-2017
https://dl.acm.org/doi/10.1145/3162957.3162963
Yadollahi AShahraki AZaiane O(2017)Current State of Text Sentiment Analysis from Opinion to Emotion MiningACM Computing Surveys10.1145/305727050:2(1-33)Online publication date: 25-May-2017
https://dl.acm.org/doi/10.1145/3057270
Rakshit RReddy VDeshpande P(2016)Emotion detection and recognition using HRV features derived from photoplethysmogram signalsProceedings of the 2nd workshop on Emotion Representations and Modelling for Companion Systems10.1145/3009960.3009962(1-6)Online publication date: 16-Nov-2016
https://dl.acm.org/doi/10.1145/3009960.3009962
Binali HPotdar VPotdar VMukhopadhyay D(2012)Emotion detection state of the artProceedings of the CUBE International Information Technology Conference10.1145/2381716.2381812(501-507)Online publication date: 3-Sep-2012
https://dl.acm.org/doi/10.1145/2381716.2381812
Ho DCao T(2012)A high-order hidden Markov model for emotion detection from textual dataProceedings of the 12th Pacific Rim conference on Knowledge Management and Acquisition for Intelligent Systems10.1007/978-3-642-32541-0_8(94-105)Online publication date: 6-Sep-2012
https://dl.acm.org/doi/10.1007/978-3-642-32541-0_8

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A Hybrid Model for Emotion Detection from Text

Detecting implicit expressions of emotion in text: A comparative analysis

Building and Exploiting EmotiNet, a Knowledge Base for Emotion Detection Based on the Appraisal Theory Model

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