Çevrimiçi Yemek Siparişine İlişkin Paylaşım Yapan Twitter Kullanıcılarının Ağ Yapısının Analizi

Yıl 2024, , 14 - 48, 29.02.2024

Yıldırım Güneş , Murat Arıkan

https://doi.org/10.5824/ajite.2024.01.002.x

Öz

Twitter gibi sosyal medya platformlarından çekilen veri setlerinin analiz sonuçlarının, yönlendirici etkilerden arındırılarak doğru şekilde yorumlanabilmesi, sosyal medya platformlarında marka görünürlüğünün artırılabilmesi maksadıyla platformlardaki etkili aktörlerin tespit edilmesi gerekir. Bunun için kullanılabilecek en uygun araçlardan biri ağ analizidir. Bu çalışmada çevrimiçi yemek siparişi konusunda Twitter’dan toplanan veri setinin ağ analiz yöntem ve teknikleri ile analizi yapılmış, kullanılan farklı ölçüm araçları ve algoritmaların sonuçları karşılaştırılmıştır. Ağ yapısı içindeki etkili kullanıcıların yerel ve küresel merkezilik değerleri hibrit bir yaklaşımla belirlenmiştir. Kullanıcılar için, altı merkezilik değerine dayalı ağırlıklı ortalama hesaplaması yapılmış, buna bağlı sıralamanın ortalama ve medyan değerlerine bağlı sıralamalarla benzerlik analizi yapılmıştır. Çalışmayla, anahtar kelimelerle oluşturulmuş bir veri setinin, ilişkisel bir yöntem olan ağ analiz yöntemi ile nasıl analiz edilebileceği gösterilmiştir. Veri seti olarak 1 Ocak-31 Aralık 2020 tarih aralığında paylaşılmış toplam 35 428 adet tweet, Python programlama dili ve NetwokX kütüphanesi kullanılarak analiz edilmiştir. Çalışma sonunda, çevrimiçi yemek siparişine ilişkin Twitter’daki paylaşımların gerçek kullanıcılara ait olup olmadığı, Twitter gündemini sektörel olarak etkileyebilme gücüne sahip merkezi konumdaki aktör ve topluluklar, paylaşımlardaki bilgi dağılımının etkinlik ve iletişimin gücü tespit edilmiştir. Yapılan tespitler, işletme kaynaklarının doğru hedef kitlelere yönlendirilmesini sağlayarak karar vericiler için etkili bir araç olarak kullanılabilecektir. Çalışmanın literatürde bu alandaki boşluğun kapatılmasına katkı sağlayacağı, benzer çalışmaların başka alanlardan elde edilmiş veri setleri üzerinde de yapılması konusunda motivasyon sağlayabileceği, sosyal medya analizlerinde ihmal edilen ve sosyal ağlarda gözle görülmeyen yönlendirici paylaşımların tespit edilmesi konusunda ağ analizinin gerekliliğine dikkat çekilebileceği düşünülmektedir.

Anahtar Kelimeler

Twitter Ağ Analizi, Sosyal Ağ Analizi, NetworkX, Ağ Yapıları, Çevrimiçi Yemek Siparişi

Network Analysis of Twitter Users Posting on Online Food Ordering

Öz

In order to interpret the findings from the analysis of the data sets obtained from social media platforms such as Twitter correctly, free from manipulations, and to increase the visibility of brands on social media platforms, effective actors on the platforms should be identified. This study analyzes the data set collected from Twitter on online food ordering with network analysis methods and techniques and compares the results of different measurement tools and algorithms used during the analysis. Local and global centrality values of influential users within the network structure are determined with a hybrid approach. For users, a weighted average was calculated based on the six centrality values, and a similarity analysis was performed with the rankings based on the mean and median values of the ranking. It is shown how a data set created with keywords can be analyzed with the network analysis method, which is a relational method. In this study, the data taken from a total of 35 428 tweets shared between January 1 and December 31, 2020, was analyzed using the Python programming language and NetwokX library. At the end of the study, it was determined whether the posts on Twitter about online food ordering belong to real users, the central actors and communities that have the power to influence the Twitter public opinion sectorally, the effectiveness of information dissemination in the posts, and the power of communication. The findings can be used as an effective tool for decision-makers by directing business resources to the right target community. It is thought that the study will contribute to filling the gap in this field in the literature, provide motivation for similar studies to be carried out on data sets obtained from other fields, and draw attention to the necessity of network analysis in detecting manipulative shares that are neglected in social media analyses and invisible in social networks.

Anahtar Kelimeler

Twitter Network Analysis, Social Network Analysis, NetworkX, Network Structures, Online Meal Order

Kaynakça

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