Gender-Based Analysis of User Reactions to Facebook Posts

Yassine El Moudene; Jaafar Idrais; Rida El Abassi; Abderrahim Sabour

doi:10.26599/BDMA.2023.9020005

Big Data Mining and Analytics 2024, 7(1): 75-86 https://doi.org/10.26599/BDMA.2023.9020005

Open Access | Issue | Published: 25 December 2023

Gender-Based Analysis of User Reactions to Facebook Posts

Show Author's Information Hide Author's Information Yassine El Moudene^¹(

), Jaafar Idrais^¹, Rida El Abassi^¹, Abderrahim Sabour^²

1Mathematical Engineering and Computer Science Laboratory, Faculty of Sciences, Ibn Zohr University, Agadir 8706, Morocco

2Department of Computer Science Mathematical−High School of Technology, Ibn Zohr University, Agadir 8706, Morocco

Keywords:

data mining, social media, gender, profiling, knowledge extraction, emotion mining, data crawling, Facebook reactions

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

Download citation

EndNote(RIS)

BibTeX

238

Views

Downloads

Citations

Crossref

WoS

Scopus

CSCD

Abstract Full text About this article

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?

Full text

Abstract

Full text

Outline

About this article

Gender-Based Analysis of User Reactions to Facebook Posts

Show Author's information Hide Author's Information Yassine El Moudene^¹(

), Jaafar Idrais^¹, Rida El Abassi^¹, Abderrahim Sabour^²

1Mathematical Engineering and Computer Science Laboratory, Faculty of Sciences, Ibn Zohr University, Agadir 8706, Morocco

2Department of Computer Science Mathematical−High School of Technology, Ibn Zohr University, Agadir 8706, Morocco

Abstract

Keywords: data mining, social media, gender, profiling, knowledge extraction, emotion mining, data crawling, Facebook reactions

References(56)

[1]

J. Idrais, Y. El Moudene, and A. Sabour, Characterizing user behavior in online social networks: Analysis of the regular use of facebook, Int. J. Electr. Comput. Eng., vol. 11, no. 4, pp. 3329–3337, 2021.

DOI Google Scholar

[2]

Y. El Moudene, J. Idrais, and A. Sabour, Introduction to sociology of online social networks in morocco. data acquisition process: Results and connectivity analysis, in Lecture Notes in Real-Time Intelligent Systems, J. Mizera-Pietraszko, P. Pichappan, and L. Mohamed, eds. Cham, Switzerland: Springer, 2017, pp. 409–418.

DOI

[3]

M. A. Wani, N. Agarwal, S. Jabin, and S. Z. Hussain, User emotion analysis in conflicting versus non-conflicting regions using online social networks, Telematics Inf., vol. 35, no. 8, pp. 2326–2336, 2018.

DOI Google Scholar

[4]

F. Benrouba and R. Boudour, Emotional sentiment analysis of social media content for mental health safety, Soc. Netw. Anal. Min., vol. 13, no. 1, p. 17, 2023.

DOI Google Scholar

[5]

M. A. Wani, P. Bours, N. Agarwal, and S. Jabin, Emotion-based mining for gender prediction in online social networks, in Proc. ACM Int. Conf. Machine Learning and Data Science, Virtual Event, 2019.

[6]

J. Idrais, Y. El Moudene, and A. Sabour, Online social networks: Study and validation of the regular behaviors of a targeted community on a complex network using a time series approach, in Proc. 4^th World Conf. Complex Systems, Ouarzazate, Morocco, 2019, pp. 1–7.

DOI

[7]

Y. El Moudene, J. Idrais, R. El Abbassi, and A. Sabour, Virtual communities homophily based on users posts in online social networks. case study: 198 facebook public groups, in Artificial Intelligence and Smart Environment, Y. Farhaoui, A. Rocha, Z. Brahmia, and B. Bhushab, eds. Cham, Switzerland: Springer, 2023, pp. 854–860.

DOI

[8]

F. T. Giuntini, L. P. Ruiz, L. De Fátima Kirchner, D. A. Passarelli, M. De Jesus Dutra Dos Reis, A. T. Campbell, and J. Ueyama, How do I feel? Identifying emotional expressions on facebook reactions using clustering mechanism, IEEE Access, vol. 7, pp. 53909–53921, 2019.

DOI Google Scholar

[9]

K. Waters, A muscle model for animation three-dimensional facial expression, ACM SIGGRAPH Comput. Graph., vol. 21, no. 4, pp. 17–24, 1987.

DOI Google Scholar

[10]

B. Weiner, A cognitive (attribution)-emotion-action model of motivated behavior: An analysis of judgments of help-giving. J. Pers. Soc. Psychol., vol. 39, no. 2, pp. 186–200, 1980.

DOI Google Scholar

[11]

R. Plutchik, A general psychoevolutionary theory of emotion, in Theories of Emotion, R. Plutchik and H. Kellerman, eds. Amsterdam, the Netherlands: Elsevier, 1980, pp. 3–33.

DOI

[12]

K. Gray and D. M. Wegner, Dimensions of moral emotions, Emotion Rev., vol. 3, no. 3, pp. 258–260, 2011.

DOI Google Scholar

[13]

D. Cicchetti, B. P. Ackerman, and C. E. Izard, Emotions and emotion regulation in developmental psychopathology, Dev. Psychopathol., vol. 7, no. 1, pp. 1–10, 1995.

DOI Google Scholar

[14]

C. E. Izard, E. M. Woodburn, K. J. Finlon, E. S. Krauthamer-Ewing, S. R. Grossman, and A. Seidenfeld, Emotion knowledge, emotion utilization, and emotion regulation, Emotion Rev., vol. 3, no. 1, pp. 44–52, 2011.

DOI Google Scholar

[15]

J. A. Russell, A circumplex model of affect, J. Pers. Soc. Psychol., vol. 39, no. 6, pp. 1161–1178, 1980.

DOI Google Scholar

[16]

J. Posner, J. A. Russell, and B. S. Peterson, The circumplex model of affect: An integrative approach to affective neuroscience, cognitive development, and psychopathology, Dev. Psychopathol., vol. 17, no. 3, pp. 715–734, 2005.

DOI Google Scholar

[17]

C. Darwin, The expression of the emotions in man and animals, Journal of Nervous & Mental Disease. doi: 10.7208/chicago/9780226220802.001.0001.

DOI

[18]

P. Ekman and R. J. Davidson, The Nature of Emotion : Fundamental Questions. Oxford, UK: Oxford University Press, 1994.

[19]

P. Ekman, Facial expression and emotion, Am. Psychol., vol. 48, no. 4, pp. 384–392, 1993.

DOI Google Scholar

[20]

J. Idrais, R. El Abassi, Y. El Moudene, and A. Sabour, Characterizing community behavior in OSNs: Modeling and forecasting activity on facebook using the SARIMA model, J. Intell. Fuzzy Syst., vol. 43, no. 3, pp. 3757–3769, 2022.

DOI Google Scholar

[21]

J. Idrais, Y. El Moudene, and A. Sabour, Introduction to sociology of Moroccan online social networks: Evolution analysis of the Moroccan community activity on facebook, in Lecture Notes in Real-Time Intelligent Systems, J. Mizera-Pietraszko, P. Pichappan, and L. Mohamed, eds. Cham, Switzerland: Springer, 2019, pp. 395–408.

DOI

[22]

J. Idrais, Y. El Moudene, R. El Abassi, and A. Sabour, The use of online social networks: Comparing Moroccan and French communities on facebook, in Artificial Intelligence and Smart Environment, Y. Farhaoui, A. Rocha, Z. Brahmia, and B. Bhushab, eds. Cham, Switzerland: Springer, 2023, pp. 890–895.

DOI

[23]

Y. Tian, T. Galery, G. Dulcinati, E. Molimpakis, and C. Sun, Facebook sentiment: Reactions and emojis, in Proc. 5^th Int. Workshop on Natural Language Processing for Social Media, Valencia, Spain, 2017, pp. 11–16.

DOI

[24]

P. Wisniewski, K. Badillo-Urquiola, Z. Ashtorab, and J. Vitak, Happiness and fear: Using emotions as a lens to disentangle how users felt about the launch of facebook reactions, ACM Trans. Soc. Comput., vol. 3, no. 4, p. 20, 2020.

DOI Google Scholar

[25]

R. A. Varanasi, E. Dicicco, and A. Gambino, Facebook reactions: Impact of introducing new features of SNS on social capital, in Proc. 20^th Int. Conf. Human-Computer Interaction, Las Vegas, NV, USA, 2018, pp. 444–451.

DOI

[26]

C. Freeman, H. Alhoori, and M. Shahzad, Measuring the diversity of facebook reactions to research, Proc. ACM on Hum.-Comput. Int., vol. 4, no. GROUP, p. 12, 2020.

DOI Google Scholar

[27]

P. Ekman, Basic emotions, in Handbook of Cognition and Emotion, T. Dalgleish and M. J. Power, eds. Chichester, UK: John Wiley & Sons, 1999, p. 16.

DOI

[28]

C. Pool and M. Nissim, Distant supervision for emotion detection using facebook reactions, in Proc. Workshop on Computational Modeling of People’s Opinions, Personality, and Emotions in Social Media, Osaka, Japan, 2016, pp. 30–39.

[29]

J. N. Matias, M. Steiner, and A. Rickman, Who gets to use facebook’s rainbow’pride’reaction, The Atlantic, https://www.theatlantic.com/technology/archive/2017/06/facebook-pride-reaction/531633/, 2017.

[30]

K. Sender, The gay market is dead, long live the gay market: From identity to algorithm in predicting consumer behavior, Advertising Soc. Quart., DOI: 10.1353/asr.2018.0001.

DOI

[31]

J. F. K. Djaha and A. Bekelynck, Fake news at Covid-19: between global circulation and political uses of the disease on Facebook in the ivorian electoral context, Les Cahiers du numerique, vol. 17, nos. 3&4, pp. 163–190, 2021.

DOI Google Scholar

[32]

Y. El Moudene, J. Idrais, and A. Sabour, The effect of keywords used on content attraction in complex networks, Complex Syst., vol. 29, no. 3, pp. 689–709, 2020.

DOI Google Scholar

[33]

R. El Abassi, J. Idrais, Y. El Moudene, and A. Sabour, Multivariate time series forecasting using recurrent neural network for a complex system, in Artificial Intelligence and Smart Environment, Y. Farhaoui, A. Rocha, Z. Brahmia, and B. Bhushab, eds. Cham, Switzerland: Springer, 2023, pp. 649–654.

DOI

[34]

Y. El Moudene, J. Idrais, and A. Sabour, Principal component analysis (PCA) use for keywords research characterization. case study: Environment and renewable energy community interest, in Proc. 4^th World Conf. Complex Systems, Ouarzazate, Morocco, 2019, pp. 1–7.

DOI

[35]

J. M. Eberl, P. Tolochko, P. Jost, T. Heidenreich, and H. G. Boomgaarden, What’s in a post? How sentiment and issue salience affect users’ emotional reactions on facebook, J. Inf. Technol. Polit., vol. 17, no. 1, pp. 48–65, 2020.

DOI Google Scholar

[36]

P. Jost, M. Maurer, and J. Haßler, Populism fuels love and anger: The impact of message features on users’ reactions on facebook, Int. J. Commun., vol. 14, pp. 2081–2102, 2020.

Google Scholar

[37]

C. Freeman, M. K. Roy, M. Fattoruso, and H. Alhoori, Shared feelings: Understanding facebook reactions to scholarly articles, in Proc. 2019 ACM/IEEE Joint Conf. Digital Libraries, Champaign, IL, USA, 2019, pp. 301–304.

DOI

[38]

A. O. Larsson, Diversifying likes: Relating reactions to commenting and sharing on newspaper facebook pages, Journalism Pract., vol. 12, no. 3, pp. 326–343, 2018.

DOI Google Scholar

[39]

A. Basile, T. Caselli, F. Merenda, and M. Nissim, Facebook reactions as controversy proxies: Predictive models over Italian news, Ital. J. Comput. Linguist., vol. 4, no. 2, pp. 73–90, 2018.

DOI Google Scholar

[40]

A. Sriteja, P. Pandey, and V. Pudi, Controversy detection using reactions on social media, in Proc. 2017 IEEE Int. Conf. Data Mining Workshops, New Orleans, LA, USA, 2017, pp. 884–889.

DOI

[41]

DOI

[42]

I. Badache and M. Boughanem, Emotional social signals for search ranking, in Proc. 40^th Int. ACM SIGIR Conf. Research and Development in Information Retrieval, Shinjuku, Tokyo, Japan, 2017, pp. 1053–1056.

DOI

[43]

N. N. Bazarova, Y. H. Choi, V. S. Sosik, D. Cosley, and J. Whitlock, Social sharing of emotions on facebook: Channel differences, satisfaction, and replies, in Proc. 18^th ACM Conf. Computer Supported Cooperative Work & Social Computing, Vancouver, Canada, 2015, pp. 154–164.

DOI

[44]

F. Krebs, B. Lubascher, T. Moers, P. Schaap, and G. Spanakis, Social emotion mining techniques for facebook posts reaction prediction, in Proc. 10^th Int. Conf. Agents and Artificial Intelligence, Funchal, Portugal, 2017, pp. 211–220.

DOI

[45]

K. Vaccaro, C. Sandvig, and K. Karahalios, “at the end of the day facebook does what ItWants”: How users experience contesting algorithmic content moderation, Proc. ACM Hum.-Comput. Int., vol. 4, no. CSCW2, p. 167, 2020.

DOI

[46]

J. Idrais, Y. El Moudene, and A. Sabour, Characterizing user behavior in online social networks: Study of seasonal changes in the Moroccan community on facebook, in Proc. 2019 3^rd Int. Conf. Intelligent Computing in Data Sciences, Marrakech, Morocco, 2019, pp. 1–5.

DOI

[47]

J. Raffo and G. Lax-Martinez, WGND 1.0, https://doi.org/10.7910/DVN/YPRQH8, 2018.

[48]

R. Gerodimos and J. Justinussen, Obama’s 2012 facebook campaign: Political communication in the age of the like button, J. Inf. Technol. Polit., vol. 12, no. 2, pp. 113–132, 2015.

DOI Google Scholar

[49]

C. Y. Chin, H. P. Lu, and C. M. Wu, Facebook users’ motivation for clicking the “like” button, Soc. Behav. Pers. Int. J., vol. 43, no. 4, pp. 579–592, 2015.

DOI Google Scholar

[50]

V. Eranti and M. Lonkila, The social significance of the facebook like button, First Monday. doi: 10.5210/fm.v20i6.5505.

DOI

[51]

H. Tuttle, Facebook scandal raises data privacy concerns, Risk Manage., vol. 65, no. 5, pp. 6–9, 2018.

Google Scholar

[52]

A. J. Brown, “Should I stay or should I leave?”: Exploring (Dis) continued facebook use after the Cambridge analytica scandal, Soc. Med.+Soc.. doi: 10.1177/2056305120913884.

DOI

[53]

G. M. Masullo and J. Kim, Exploring “angry” and “like” reactions on uncivil facebook comments that correct misinformation in the news, Digital Journalism, vol. 9, no. 8, pp. 1103–1122, 2021.

DOI Google Scholar

[54]

V. L. Parsons, stratified sampling, http://onlinelibrary.wiley.com/doi/full/10.1002/9781118445112.stat05999.pub2, 2023.

[55]

H. Taherdoost, Sampling methods in research methodology; how to choose a sampling technique for research, Ssrn Electronic Journal. doi: 10.2139/ssrn.3205035.

DOI

[56]

G. Sharma, Pros and cons of different sampling techniques, Int. J. Appl. Res., vol. 3, no. 7, pp. 749–752, 2017.

Google Scholar

About this article

Publication history

Rights and permissions

Publication history

Received: 03 December 2022

Revised: 03 April 2023

Accepted: 24 April 2023

Published: 25 December 2023

Issue date: March 2024

Copyright

Rights and permissions

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/).