METİN MADENCİLİĞİ VE WENSLO-LODECI YÖNTEMLERİ İLE KULLANICI DENEYİMİ ANALİZİ: KARGO MOBİL UYGULAMALARI ÖRNEGİ

Yıl 2026, Sayı: Advanced Online Publication, 149 - 167

Alparslan Oğuz , Yunus Emre Özenoğlu , Okan Alkan

https://doi.org/10.46482/ebyuiibfdergi.1816735

Öz

Bu çalışmada, kargo firmalarının mobil uygulamalarında kullanıcı deneyimleri metin madenciliği ve çok kriterli karar verme (ÇKKV) yöntemleri ile analiz edilmiştir. Google Play ve App Store üzerinden toplanan kullanıcı yorumları, performans kriterlerinin belirlenmesi ve stratejik önerilerin geliştirilmesi amacıyla detaylı bir şekilde incelenmiştir. Elde edilen bulgular, özellikle TrendyolExpress’in kullanıcı memnuniyetinde diğer firmalara göre belirgin bir üstünlük sağladığını gösterirken Hepsijet ve Yurtiçi Kargo’nun iyileştirme alanları bulunduğunu ortaya koymaktadır. Metin madenciliği ile yapılan bigram analizleri, kullanıcı deneyimlerini derinlemesine anlamada önemli bir araç olarak işlev görmektedir. WENSLO ve LODECI yöntemlerinin uygulanması sonucunda SDB ve TP+ kriterlerinin, müşteri memnuniyetinin artırılmasında belirleyici olduğu tespit edilmiştir. Sonuç olarak bu çalışma, kargo firmalarının kullanıcı deneyimlerini geliştirmeye yönelik stratejik süreçlerde kullanılabilecek somut ve bilimsel bir temel sunmaktadır.

Anahtar Kelimeler

Metin Madenciliği , Kullanıcı Deneyimi , Çok Kriterli Karar Verme

USER EXPERIENCE ANALYSIS USING TEXT MINING AND THE WENSLO-LODECI METHODS: THE CASE OF MOBILE CARGO APPLICATIONS

Öz

This study analyzes user experiences in the mobile applications of cargo companies by integrating text mining and multi-criteria decision-making (MCDM) methods. User reviews collected from Google Play and the App Store were examined in detail to identify performance criteria and to develop strategic recommendations. The findings indicate that TrendyolExpress exhibits a notable superiority over other firms in terms of user satisfaction, while Hepsijet and Yurtiçi Kargo have identifiable areas for improvement. Bigram analyses conducted through text mining functioned as an effective tool for gaining an in-depth understanding of user experiences. As a result of applying the WENSLO and LODECI methods, it was determined that the SDB and TP+ criteria are the most decisive factors in enhancing customer satisfaction. In conclusion, this study provides a concrete and scientific basis that can be utilized in strategic processes aimed at improving user experiences in cargo companies.

Anahtar Kelimeler

Text Mining , User Experience , Multi-Criteria Decision-Making

Kaynakça

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