Kocaeli Journal of Science and Engineering

Yazarlar: Emel OKKALI, Hilmiye ATAMTÜRK, Zeynep Hilal KİLİMCİ

Konular:Bilgisayar Bilimleri, Yapay Zeka

DOI:10.34088/kojose.907333

Anahtar Kelimeler:Violence aganist/to Women,Opinion Mining,Latent Dirichlet Allocation,Social Media Mining,Topic Modeling

Özet: In recent times, people's reactions to violence against women, harassment and murder have been shared more and more, thanks to social media. This, in turn, led to the organization of people and increased awareness of violence against women. Inspired by this study, it focuses on subject modeling techniques to determine people's perspectives on violence against women, which is growing day by day. Opinions from users about violence against women are collected using the social media platform Twitter in order to analyze the reaction of the society. After the preprocessing stage, Turkish tweets are analyzed using Latent Semantic Analysis (LSA), Latent Dirichlet Allocation (LDA), Hierarchical Dirichlet Process (HDP), Non-Negative Matrix Factorization (NMF) techniques. The results of the experiment show that the LDA technique significantly reveals the reaction of the society to violence against women and social awareness in Turkey.

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