Gender-Based Analysis of User Reactions to Facebook Posts
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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Tsinghua University Press
2024-03-01
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| Series: | Big Data Mining and Analytics |
| Subjects: | |
| Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2023.9020005 |
| _version_ | 1797370337368735744 |
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| author | Yassine El Moudene Jaafar Idrais Rida El Abassi Abderrahim Sabour |
| author_facet | Yassine El Moudene Jaafar Idrais Rida El Abassi Abderrahim Sabour |
| author_sort | Yassine El Moudene |
| collection | DOAJ |
| description | 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? |
| first_indexed | 2024-03-08T18:01:03Z |
| format | Article |
| id | doaj.art-31caa3b586b54bbca201327e8de868f7 |
| institution | Directory Open Access Journal |
| issn | 2096-0654 |
| language | English |
| last_indexed | 2024-03-08T18:01:03Z |
| publishDate | 2024-03-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | Big Data Mining and Analytics |
| spelling | doaj.art-31caa3b586b54bbca201327e8de868f72024-01-02T01:34:00ZengTsinghua University PressBig Data Mining and Analytics2096-06542024-03-0171758610.26599/BDMA.2023.9020005Gender-Based Analysis of User Reactions to Facebook PostsYassine El Moudene0Jaafar Idrais1Rida El Abassi2Abderrahim Sabour3Mathematical Engineering and Computer Science Laboratory, Faculty of Sciences, Ibn Zohr University, Agadir 8706, MoroccoMathematical Engineering and Computer Science Laboratory, Faculty of Sciences, Ibn Zohr University, Agadir 8706, MoroccoMathematical Engineering and Computer Science Laboratory, Faculty of Sciences, Ibn Zohr University, Agadir 8706, MoroccoDepartment of Computer Science Mathematical−High School of Technology, Ibn Zohr University, Agadir 8706, MoroccoOnline 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?https://www.sciopen.com/article/10.26599/BDMA.2023.9020005profilingknowledge extractiondata miningemotion miningsocial mediadata crawlingfacebook reactionsgender |
| spellingShingle | Yassine El Moudene Jaafar Idrais Rida El Abassi Abderrahim Sabour Gender-Based Analysis of User Reactions to Facebook Posts Big Data Mining and Analytics profiling knowledge extraction data mining emotion mining social media data crawling facebook reactions gender |
| title | Gender-Based Analysis of User Reactions to Facebook Posts |
| title_full | Gender-Based Analysis of User Reactions to Facebook Posts |
| title_fullStr | Gender-Based Analysis of User Reactions to Facebook Posts |
| title_full_unstemmed | Gender-Based Analysis of User Reactions to Facebook Posts |
| title_short | Gender-Based Analysis of User Reactions to Facebook Posts |
| title_sort | gender based analysis of user reactions to facebook posts |
| topic | profiling knowledge extraction data mining emotion mining social media data crawling facebook reactions gender |
| url | https://www.sciopen.com/article/10.26599/BDMA.2023.9020005 |
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