A Survey of Social Emotion Prediction Methods

Abdullah Alsaedi; Phillip Brooker; Floriana Grasso; Stuart Thomason

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Paper

A Survey of Social Emotion Prediction Methods

Topics: Data Analytics; Data Mining; Neural Network Applications; Predictive Modeling; Social Data Analytics; Support Vector Machines; Text Analytics

In Proceedings of the 10th International Conference on Data Science, Technology and Applications DATA - Volume 1, 223-230, 2021

Authors: Abdullah Alsaedi ¹ ; Phillip Brooker ² ; Floriana Grasso ¹ and Stuart Thomason ¹

Affiliations: ¹ Department of Computer Science, University of Liverpool, U.K. ; ² Department of Sociology, Social Policy and Criminology, University of Liverpool, U.K.

Keyword(s): Social Emotion Prediction Methods, Social Emotion, Reader’s Emotion.

Abstract: Emotions are an important factor that affects our communication. Considerable research has been done to detect and classify emotion in text. However, most deal with emotion from the writer’s perspective. Social emotion is the emotion of the reader when exposed to the text. With the increased use of social media, many works are performed for social emotion prediction. In this paper, we attempt to provide a survey of social emotion prediction methods. To the best of our knowledge, this is the first work to survey the literature of social emotion, review methods, and used techniques, compare the methods, and highlight their limitations.

CC BY-NC-ND 4.0

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Paper citation in several formats:

Alsaedi, A.; Brooker, P.; Grasso, F. and Thomason, S. (2021). A Survey of Social Emotion Prediction Methods. In Proceedings of the 10th International Conference on Data Science, Technology and Applications - DATA; ISBN 978-989-758-521-0; ISSN 2184-285X, SciTePress, pages 223-230. DOI: 10.5220/0010546902230230

@conference{data21,
author={Abdullah Alsaedi. and Phillip Brooker. and Floriana Grasso. and Stuart Thomason.},
title={A Survey of Social Emotion Prediction Methods},
booktitle={Proceedings of the 10th International Conference on Data Science, Technology and Applications - DATA},
year={2021},
pages={223-230},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010546902230230},
isbn={978-989-758-521-0},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Data Science, Technology and Applications - DATA
TI - A Survey of Social Emotion Prediction Methods
SN - 978-989-758-521-0
IS - 2184-285X
AU - Alsaedi, A.
AU - Brooker, P.
AU - Grasso, F.
AU - Thomason, S.
PY - 2021
SP - 223
EP - 230
DO - 10.5220/0010546902230230
PB - SciTePress