Towards using Multimodal Features of Social Networks for Improved Contextual Emotion Detection

Ahmed S. Rizk, Sherif G. Aly, Mohamed Shalan

Abstract

Social networks are valuable source of information that could be used in classifying users’ emotions. In this paper, we explore the importance of certain multimodal features of social networks, other than text, that can be used in enhancing emotion detection. We study the types of posts, the degree of interaction with contacts, and the influence of contact opinions and how they tend to affect the emotions of social network users. We conducted an online survey targeting Facebook users to know how they are affected by such features. The results of our study show that status messages are the most used feature to express the social network users’ emotions, and the emotions of social network user are affected by posts and updates from friends, especially close friends. The number of likes expressed to social network users was found to positively affect their emotions. We will use such findings to prototype a system for enhanced emotion detection.

References

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Paper Citation


in Harvard Style

S. Rizk A., G. Aly S. and Shalan M. (2013). Towards using Multimodal Features of Social Networks for Improved Contextual Emotion Detection . In Proceedings of the 3rd International Conference on Pervasive Embedded Computing and Communication Systems - Volume 1: PECCS, ISBN 978-989-8565-43-3, pages 113-117. DOI: 10.5220/0004305801130117


in Bibtex Style

@conference{peccs13,
author={Ahmed S. Rizk and Sherif G. Aly and Mohamed Shalan},
title={Towards using Multimodal Features of Social Networks for Improved Contextual Emotion Detection},
booktitle={Proceedings of the 3rd International Conference on Pervasive Embedded Computing and Communication Systems - Volume 1: PECCS,},
year={2013},
pages={113-117},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004305801130117},
isbn={978-989-8565-43-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Pervasive Embedded Computing and Communication Systems - Volume 1: PECCS,
TI - Towards using Multimodal Features of Social Networks for Improved Contextual Emotion Detection
SN - 978-989-8565-43-3
AU - S. Rizk A.
AU - G. Aly S.
AU - Shalan M.
PY - 2013
SP - 113
EP - 117
DO - 10.5220/0004305801130117