Şirketlerin sosyal medya metriklerini kullanıcıların oluşturduğu içerik odağında değerlendirmeye yönelik bir MCDM yaklaşımı

Year 2022, Volume: 5 Issue: 3, 266 - 285, 09.11.2022

Büşra Ayan , Seda Abacıoğlu

Abstract

Kullanıcıların oluşturduğu içerik (UGC), şirketleri tüketicilerin satın alma niyetlerinden şirketlerin satışlarına kadar etkileyen ana faktörlerden biri haline gelmiştir. Bu çalışma, şirketlerin sosyal medya ölçümlerini UGC'ye dayalı olarak değerlendirmek için bir MCDM yaklaşımı önermektedir. UGC metrikleri, her bir tweet'in duygu türüne (olumlu, olumsuz veya nötr) ve ilgili metriklere (tweet, retweet, favori ve erişim) dayalı oranlar olarak belirlenip hesaplanmıştır. Kozmetik, pazaryeri ve elektronik alanlarında faaliyet gösteren altı şirket hakkında Twitter'dan veri toplanmıştır. MCDM teknikleri, kriter ağırlıklarını elde etmek için CRITIC, şirketleri sıralamak için ARAS ve COPRAS, R programlama dilinde uygulanmıştır. Bu çalışmanın bulguları, UGC aracılığıyla şirketlerin sıralamasının iyileştirilmesine ve konuyla ilgili literatürün genişletilmesine katkıda bulunmaktadır. MCDM yaklaşımı birkaç özelliği bir arada dikkate aldığından dolayı şirketlerin sosyal medya metriklerinin değerlendirilmesinde etkili bir şekilde kullanılması tavsiye edilmiştir. Veri analizi için R kodları ekte verilmiştir. Bu yaklaşım birkaç özelliği bir arada dikkate aldığı için MCDM tekniklerinin, şirketlerin sosyal medya metriklerini değerlendirmek için etkili bir şekilde kullanılması tavsiye edilmiştir. Veri analizi için R kodları da ekte verilmiştir.

Keywords

Sosyal Medya, Kullanıcıların Oluşturduğu İçerik, CRITIC, ARAS, COPRAS

An MCDM approach to evaluating companies’ social media metrics based on user-generated content

Abstract

User-generated content (UGC) has become one of the main factors that impacts companies, from consumers’ purchase intentions to sales. This study proposes an MCDM approach to evaluate companies’ social media metrics based on UGC. UGC metrics were defined and calculated as ratios based on each tweet’s sentiment type (positive, negative, or neutral) and relevant metrics (tweet, retweet, favorite, and reach). Data was gathered from Twitter about six companies operating in cosmetics, marketplace, and electronics. MCDM techniques were conducted in the R programming language, namely CRITIC for obtaining criteria weights and ARAS and COPRAS for ranking the companies. The findings of this study contribute to improving the ranking of companies through UGC and extend the literature on the subject. MCDM techniques are recommended to be used effectively to evaluate companies’ social media metrics since this approach considers several attributes altogether. R codes for data analysis are also provided in the appendix.

Keywords

Social Media, User-Generated Content, CRITIC, ARAS, COPRAS

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