BİR METİN MADENCİLİĞİ UYGULAMASI: VOSVIEWER

Year 2020, Volume: 8 Issue: 2, 344 - 354, 31.08.2020

Murat Artsın

Abstract

Geçmişten günümüze kadar veri ve veri yığınlarından anlamlı bilgilerin üretilme çabası artarak devam etmektedir. Büyük veriden anlamlı bilginin üretilme sürecinde araştırmacıların üzerinde durduğu yaklaşımlardan birisi olarak görselleştirme, son yıllarda oldukça ilgi toplamış ve bir çok farklı alanda yaygınlaşmaya başlamıştır. Durum böyle olunca, veri madenciliğinde karmaşık ilişkilerin ortaya çıkarıldığı bibliyometri analizi çalışmalarında da elde edilen verinin görselleştirilmesi ve görselleştirme yaklaşımlarının incelenmesi önemli bir konu haline gelmiştir. Bu çalışmada, bibliyometrik ağların görselleştirilmesinde kullanılan ve aynı zamanda metinler içerisindeki kelime ve kelime öbeklerinin ilişkisini ortaya çıkarmaya yarayan başka bir ifade ile metin madenciliği uygulaması olan VOSviewer programının kullanımı incelenecektir. Bu inceleme ile birlikte veri madenciliği kapsamında kullanımına yönelik bilgilendirici yönlendirmelere yer verilecektir.

Keywords

Veri madenciliği, Metin madenciliği, Bibliyometrik analiz, VOSviewer

A TEXT MINING APPLICATION: VOSVIEWER

Abstract

From past to present, efforts to produce meaningful information from data and data stacks increasingly continue. Visualization, as one of the approaches emphasized by researchers in the process of producing meaningful information from big data, has gained great interest in recent years and has become widespread in many different fields. As such, the visualization of data obtained in bibliometric analysis studies revealing complex relationships in data mining and examination of visualization approaches have become an important issue. In this study, the use of VOSviewer program, being a text mining application, used to visualize bibliometric networks and also used to reveal the relationship between words and phrases in the texts, will be examined. This technical note will include informative directions for the use of data mining.

Keywords

Data mining,, Text mining,, Bibliometric analysis,, VOSviewer

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