Estimation With Artificial Neural Network on Electronic Word of Mouth: Opinion Searching

Yıl 2020, Cilt: 18 Sayı: 35, 183 - 207, 31.01.2020

İbrahim Topal

https://doi.org/10.35408/comuybd.604645

Öz

Today's consumers see social media as a reliable
source of information and make electronic word-of-mouth (e-WOM) on this
platform by talking about products and services. In social media, e-WOM is used
in three different ways: “opinions searching”(being the most common), “opinion
giving”, and “opinion forwarding”. Identifying factors that motivate consumers
for opinion searching can make a significant contribution to the achievement of
marketing objectives of corporations. For this reason, e-WOM has been discussed
in the recent literature with various motivation factors and analysis methods.
This study differs from other research by combining motivation factors and
detailing e-WOM behavior as well as using artificial neural networks. Facebook,
most widely used social media site, was used for this study. Motivation factors
were estimated by artificial neural network method. Bayesian Regulation method
was used for the analysis. As a result showed that the performance values were
acceptable and the success rate was 90%.

Anahtar Kelimeler

Electronic Word-of-Mouth, Motivation Factors, Social Networks, Artificial Neural Networks, Bayesian Regulation

Estimation With Artificial Neural Network on Electronic Word of Mouth: Opinion Searching

Öz

Günümüz tüketicileri
sosyal medyayı güvenilir bir bilgi kaynağı olarak görmekte ve bu platformda
ürün ve hizmetler hakkında konuşarak elektronik ağızdan ağıza iletişim (E-AAİ)
gerçekleştirmektedirler. Tüketiciler sosyal medyada e-AAİ’yi “görüş arama”,
“görüş iletme” ve “görüş belirtme” olarak üç farklı şekilde yapmaktadırlar. Bu
davranışlardan en yaygın olanı ise görüş aramadır. Tüketicileri görüş aramaya
motive eden faktörlerin belirlenmesi işletmelerin pazarlama amaçlarına
ulaşılmasına önemli katkı sağlayabilir. Bu nedenle E-AAİ, literatürde çeşitli
motivasyon faktörleri ve analiz yöntemleriyle ele alınmıştır. Bu çalışma
motivasyon faktörlerini bir araya getirmesi, e-aai davranışını detaylandırması
ve yapay sinir ağlarını kullanması ile diğerlerinden farklılaşmaktadır. Çalışma
en yaygın kullanıma sahip sosyal medya sitesi Facebook temelinde
yapılmıştır.  Motivasyon faktörleri yapay
sinir ağları yöntemiyle tahmin edilmeye çalışılmıştır. Bayesian regülasyon geri
yayma ile analizi yapılmıştır. Analizler neticesinde performans değerlerinin kabul
edilebilir değerde ve başarı oranının %90 olduğu görülmüştür. 

Anahtar Kelimeler

Elektronik Ağızdan Ağıza İletişim, Motivasyon Faktörleri, Sosyal Ağlar, Yapay Sinir Ağları, Bayesian Regülasyon

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