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Open Access

Gender-Based Analysis of User Reactions to Facebook Posts

Mathematical Engineering and Computer Science Laboratory, Faculty of Sciences, Ibn Zohr University, Agadir 8706, Morocco
Department of Computer Science Mathematical−High School of Technology, Ibn Zohr University, Agadir 8706, Morocco
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Abstract

Online Social Networks (OSNs) are based on the sharing of different types of information and on various interactions (comments, reactions, and sharing). One of these important actions is the emotional reaction to the content. The diversity of reaction types available on Facebook (namely FB) enables users to express their feelings, and its traceability creates and enriches the users’ emotional identity in the virtual world. This paper is based on the analysis of 119875012 FB reactions (Like, Love, Haha, Wow, Sad, Angry, Thankful, and Pride) made at multiple levels (publications, comments, and sub-comments) to study and classify the users’ emotional behavior, visualize the distribution of different types of reactions, and analyze the gender impact on emotion generation. All of these can be achieved by addressing these research questions: who reacts the most? Which emotion is the most expressed?

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Big Data Mining and Analytics
Pages 75-86
Cite this article:
El Moudene Y, Idrais J, El Abassi R, et al. Gender-Based Analysis of User Reactions to Facebook Posts. Big Data Mining and Analytics, 2024, 7(1): 75-86. https://doi.org/10.26599/BDMA.2023.9020005

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Received: 03 December 2022
Revised: 03 April 2023
Accepted: 24 April 2023
Published: 25 December 2023
© The author(s) 2023.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

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