Sentiment Analysis on Women’s Rights Discussions in Turkish Social Media Using Machine Learning Methods

Mustafa Çataltaş; Ayşenur Arslan; Nurdan Akhan Baykan

doi:10.35377/saucis...1898109

Sentiment Analysis on Women’s Rights Discussions in Turkish Social Media Using Machine Learning Methods

Abstract

Gender-based legal protections and women’s rights frameworks have been a major topic of public debate in Türkiye, with intense discussions occurring on social media. Understanding the sentiment behind such online discussions can help capture public perceptions and their evolution over time. Therefore, this study aims to detect sentiment in Turkish socio-political posts using machine learning techniques. A total of 15,943 posts from 2010 to 2024 were collected and preprocessed, resulting in a clean dataset of 13,008 posts. Within the scope of the study, sentiments were labeled as positive, negative, or neutral using both BERT-based models, and classification was performed using basic machine learning algorithms. First, two pre-trained BERT-based models were utilized for sentiment analysis, with the selected model achieving 71.9% accuracy on a manually labeled test set. Then, further analysis was conducted using traditional machine learning algorithms, where Random Forest achieved the best performance with a 70.5% accuracy on the manually labeled test set. To analyze the perception of the human rights treaties in society, time-based sentiment shifts, especially around key political events, were visualized. The visualizations show that negative posts received more interaction than positive posts, and the number of negative posts was considerably higher than neutral and positive posts during the important dates for the issue. This study demonstrates the value of combining social media data with machine learning to interpret public opinion on significant societal debates.

Keywords

Ethical Statement

The authors declare that all scientific and ethical principles were strictly followed during the preparation of this study. All sources consulted and utilized have been appropriately acknowledged and cited in the bibliography.

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Details

Primary Language

English

Subjects

Natural Language Processing

Journal Section

Research Article

Authors

Mustafa Çataltaş ^*
0000-0002-5598-9659
Türkiye

Ayşenur Arslan
0009-0005-5239-5360
Türkiye

Nurdan Akhan Baykan
0000-0002-4289-8889
Türkiye

Early Pub Date

October 27, 2026

Publication Date

October 30, 2026

Submission Date

February 27, 2026

Acceptance Date

August 26, 2026

Published in Issue

Year 2026 Volume: 9 Number: 5

DOI

https://doi.org/10.35377/saucis...1898109

IZ

https://izlik.org/JA57MN86PW

Cite

RIS / Bibtex

APA

Çataltaş, M., Arslan, A., & Akhan Baykan, N. (2026). Sentiment Analysis on Women’s Rights Discussions in Turkish Social Media Using Machine Learning Methods. Sakarya University Journal of Computer and Information Sciences, 9(5), 1560-1570. https://doi.org/10.35377/saucis...1898109

AMA

1.Çataltaş M, Arslan A, Akhan Baykan N. Sentiment Analysis on Women’s Rights Discussions in Turkish Social Media Using Machine Learning Methods. SAUCIS. 2026;9(5):1560-1570. doi:10.35377/saucis.1898109

Chicago

Çataltaş, Mustafa, Ayşenur Arslan, and Nurdan Akhan Baykan. 2026. “Sentiment Analysis on Women’s Rights Discussions in Turkish Social Media Using Machine Learning Methods”. Sakarya University Journal of Computer and Information Sciences 9 (5): 1560-70. https://doi.org/10.35377/saucis. 1898109.

EndNote

Çataltaş M, Arslan A, Akhan Baykan N (October 1, 2026) Sentiment Analysis on Women’s Rights Discussions in Turkish Social Media Using Machine Learning Methods. Sakarya University Journal of Computer and Information Sciences 9 5 1560–1570.

IEEE

[1]M. Çataltaş, A. Arslan, and N. Akhan Baykan, “Sentiment Analysis on Women’s Rights Discussions in Turkish Social Media Using Machine Learning Methods”, SAUCIS, vol. 9, no. 5, pp. 1560–1570, Oct. 2026, doi: 10.35377/saucis...1898109.

ISNAD

Çataltaş, Mustafa - Arslan, Ayşenur - Akhan Baykan, Nurdan. “Sentiment Analysis on Women’s Rights Discussions in Turkish Social Media Using Machine Learning Methods”. Sakarya University Journal of Computer and Information Sciences 9/5 (October 1, 2026): 1560-1570. https://doi.org/10.35377/saucis. 1898109.

JAMA

1.Çataltaş M, Arslan A, Akhan Baykan N. Sentiment Analysis on Women’s Rights Discussions in Turkish Social Media Using Machine Learning Methods. SAUCIS. 2026;9:1560–1570.

MLA

Çataltaş, Mustafa, et al. “Sentiment Analysis on Women’s Rights Discussions in Turkish Social Media Using Machine Learning Methods”. Sakarya University Journal of Computer and Information Sciences, vol. 9, no. 5, Oct. 2026, pp. 1560-7, doi:10.35377/saucis. 1898109.

Vancouver

1.Mustafa Çataltaş, Ayşenur Arslan, Nurdan Akhan Baykan. Sentiment Analysis on Women’s Rights Discussions in Turkish Social Media Using Machine Learning Methods. SAUCIS. 2026 Oct. 1;9(5):1560-7. doi:10.35377/saucis. 1898109