Twitter (X)'da Alana Özgü Kanaat Önderlerinin Belirlenmesi: İyileştirilmiş Bir Yaklaşım

Year 2024, Volume: 8 Issue: 1, 65 - 81, 31.05.2024

Nurullah Karaca , Onur Ayas

https://doi.org/10.33709/ictimaiyat.1404626

Abstract

Bilginin yayılımını analiz etmek ve anlamak için Twitter'daki kanaat önderlerinin rolü göz ardı edilemez. Bilgi çağının gelişi ve sosyal ağ platformlarının ortaya çıkışı kanaat önderliğini ortadan kaldırmamış, aksine yeni biçimlerinin ortaya çıkmasına neden olmuştur. Bu doğrultuda, bu makale Twitter'daki kanaat önderlerini tespit etmeye yönelik bir yöntem önermektedir. Bu yöntem temel olarak Twitter listelerine eklenmiş kullanıcıların uzmanlıklarına tahmin etmeye yönelik anlamsal ipuçları içeren meta verilerine dayanmaktadır. Bu çalışma halihazırda kullanılan bu yöntemi temel alarak yöntemin herhangi bir uzmanlık alandaki yüksek etkili Twitter kullanıcılarını belirlemek için nasıl daha esnek bir şekilde kullanılabileceğini ayrıntılı olarak göstermektedir. Bu bağlamda, çalışmadan önerilen yöntem farklı araştırma sorularına uyarlanarak, araştırmacıların kendi amaçlarına uyacak şekilde uygulanmasına olanak tanıyacaktır. Bu çalışma ayrıca, Twitter listeleri aracılığıyla belirlenen kanaat önderlerinin nasıl sıralanabileceğine ilişkin yeni bir yaklaşım önermektedir. Bu bağlamda geliştirilen sıralama endeksi, bilgi yayılımının hem dikey (kamuoyu algısı ve etkileşimi) hem de yatay (alandaki itibarı) boyutlarına dikkate almaktadır.

Keywords

X/Twitter, Kanaat önderleri, Bilginin yayılımı, Sosyal ağlar

Identifying Domain-specific Opinion Leaders in Twitter (X): An Optimized Approach

Abstract

The role of opinion leaders on Twitter to analyze and understand the diffusion of information cannot be overlooked. The coming of the information age and the advent of social networking platforms have not eliminated opinion leadership but rather led to the emergence of its new forms. In this line, this paper deals with organically identifying opinion leaders on Twitter, based on the list feature. The method relies on the meta-data of Twitter lists, containing semantic cues to infer the topical expertise of its members. Based on the studies that have already shown the effectiveness of this method, this paper further illustrates in detail how the method can be employed flexibly to identify highly influential Twitter users in any specific domain. In this regard, the method can be adapted to different research questions, allowing researchers to apply it to suit their specific objectives and data. This paper also presents a novel approach as to how influential Twitter users identified through Twitter lists can be ranked. The ranking index proposed is attentive to both vertical (public perception and engagement) and horizontal (peer perception) dimensions of information diffusion.

Keywords

Opinion leaders, Diffusion of innovation, Social networks, X/Twitter

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