Sosyal Ağlarda Topluluk ve Konu Tespiti: Bir Sistematik Literatür Taraması

Year 2022, Volume: 15 Issue: 3, 317 - 329, 31.07.2022

Ömer Ayberk Şencan , İsmail Atacak , İbrahim Dogru

https://doi.org/10.17671/gazibtd.1061332

Cited By: 1

Abstract

Günümüzde internetin hızlı bir şekilde gelişmesi ve kolay bir şekilde ulaşılır olması; Facebook, Instagram, Twitter ve LinkedIN gibi yaygın kullanılan sosyal iletişim platformlarını büyük veri yığınlarının olduğu ortamlara dönüştürmüştür. Bu durum hem aranan bilgiye kolay bir şekilde ulaşılabilmesi için konu tespiti uygulamalarının, hem de konuyla ilgili paylaşım yapan benzer eğilim ve düşünceye sahip topluluklara toplu hizmet verebilmek için topluluk tespit uygulamalarının bu platformlarda kullanımını zorunlu hale getirmiştir. Bu yüzden araştırmacıların sosyal iletişim ağlarında konu tespiti ve topluluk tespiti alanları üzerine araştırmalar yapması ve problemin çözümü ile ilgili yöntem ve teknikler geliştirmesi bu ortamların etkin kullanımı açısından hayati bir önem arz eder. Bu çalışmada, bu alanlara kapsamlı bir bakış sağlamak için sosyal medya platformlarında konu ve topluluk analizi yapan çalışmalar üzerine sistematik ve derinlemesine bir literatür incelemesi sunulmaktadır. İncelemesi yapılacak çalışmaların çoğu uygulamada başarılı sonuçlar ürettiği bilinen makine öğrenmesi temelli modeller kullanan makalelerden seçilmiştir. Bu çalışmaların incelenmesi neticesinde; topluluk tespiti alanında elde ettiği performans değerleri ile Louvain metodunun öne çıktığı görülürken, performans açısından konu analizi alanında tek bir modelin önerilemeyeceği ve uygun modelin ancak verilen sorunun tüm özellikleri göz önünde bulundurularak, probleme özgü şekilde seçilmesi ya da oluşturulması gerektiği sonucuna varılmıştır.

Keywords

sosyal ağ, topluluk tespiti, konu tespiti, twitter, doğal dil işleme, makine öğrenmesi

Systematic Literature Review of Detecting Topics and Communities in Social Networks

Abstract

In the recent past and in today’s world, the internet is advancing rapidly and is easily accessible; this growth has made the social media platforms such as Facebook, Instagram, Twitter, and LinkedIn widely used which produces big data. This requires both topic Detection applications in order to access the required information, as well as community detection practices in order to provide collective services to communities that can be referred to as individuals with similar interests and opinions over the same subject. Therefore, it is vital for researchers to conduct research on topic detection and community detection research areas in social networks and to develop methods and techniques for problem-solving. In this study, a systematic and in-depth literature review is provided on studies that conduct topic and community analysis on social media platforms to provide a comprehensive overview of the given areas. Most of the studies to be analyzed are selected from articles using machine learning-based models that are known to achieve successful results in practice. As a result of the analysis of these studies; it has been concluded that a single model cannot be proposed in the area of topic detection and that the appropriate model should only be selected or created in a problem-specific way, taking into account all the characteristics of the given problem, while the Louvain method seems to stand out with its results in terms of performance in the area of community detection.

Keywords

social network, community detection, topic detection, twitter, natural language processing, machine learning

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