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Dergiler / Hittite Journal of Science and Engineering / 2026 / Volume: 13 Issue: 2

Correction:

Correction: Corrigendum to: A New Framework for Decentralized Social Networks: Harnessing Blockchain, Deep Learning, and NLP

Amir Al Kadah(SAKARYA ÜNİVERSİTESİ, FEN BİLİMLERİ ENSTİTÜSÜ)0009-0000-7724-7894
Deniz Balta(SAKARYA ÜNİVERSİTESİ)0000-0001-9104-1868
Sayfa
—
Yayın Tarihi
2026-06-30
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

This comprehensive integration of blockchain, deep learning, and NLP offers a transformative approach to social networking, promoting transparency, security, and ethical standards, while creating a safer, more trustworthy digital environment.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:This paper presents a novel framework for a decentralized social network that integrates blockchain technology, natural language processing (NLP), and deep learning (DL) to address critical vulnerabilities in traditional centralized online social networks (OSNs).
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Temel Bulgular & Veri:This paper also elaborates on the implementation of these technologies, demonstrating how blockchain-based smart contracts manage secure interactions, deep learning models categorize content, and NLP techniques ensure content authenticity.
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Sonuç & Katkı:This comprehensive integration of blockchain, deep learning, and NLP offers a transformative approach to social networking, promoting transparency, security, and ethical standards, while creating a safer, more trustworthy digital environment.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Blockchain · Decentralized Social Networks · Deep Learning

Abstract

This paper presents a novel framework for a decentralized social network that integrates blockchain technology, natural language processing (NLP), and deep learning (DL) to address critical vulnerabilities in traditional centralized online social networks (OSNs). Blockchain ensures data integrity, transparency, and decentralized governance, mitigating risks associated with data manipulation and privacy breaches. Deep learning algorithms, including Bidirectional LSTM for post-category prediction and LSTM for suicide detection, enhance content management by capturing nuanced language cues and identifying distress signals. NLP techniques, such as TF-IDF vectorization and cosine similarity, further improve content originality and moderation by detecting duplicates, preventing plagiarism, and fostering diverse content. This paper also elaborates on the implementation of these technologies, demonstrating how blockchain-based smart contracts manage secure interactions, deep learning models categorize content, and NLP techniques ensure content authenticity. This comprehensive integration of blockchain, deep learning, and NLP offers a transformative approach to social networking, promoting transparency, security, and ethical standards, while creating a safer, more trustworthy digital environment.

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Bu Makaleye Atıf Yap

Kadah, A. A., Balta, D. (2026). Correction:. Hittite Journal of Science and Engineering, Volume: 13 Issue: 2. https://doi.org/10.17350/HJSE19030000381

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