Comparative Analysis of Gastronomic Images Shared on Social Media: The Case of Michelin Key Hotels

Abstract

Gastronomic images shared on social media platforms have become one of the key elements shaping the aesthetic presentation, brand image, and perceived gastronomic experience of hospitality establishments. This study comparatively examines gastronomic images shared on the social media accounts of Michelin Key hotels in Türkiye through a researcher-driven qualitative content analysis conducted using MAXQDA and an AI-assisted evaluation performed with ChatGPT Vision. The research sample consists of a total of 252 gastronomic images selected from the official Instagram accounts of 26 hotels. The images were analyzed according to nine thematic codes: color aesthetics, composition, lighting, depth of field, professionalism, authenticity, atmosphere, emotional tone, and the presence of human/hand elements. The data were coded by the researcher using MAXQDA, while the same images were uploaded to ChatGPT Vision, and the descriptive interpretations generated by the model were qualitatively compared within the same thematic framework. The findings indicate that composition, lighting, professionalism, and color aesthetics are the most dominant aesthetic elements identified in both the researcher coding and the AI-based evaluation. The results further reveal that artificial intelligence demonstrates a high level of consistency with researcher evaluations in technical aesthetic components; however, it provides more superficial interpretations in more abstract themes such as atmosphere, cultural representation, and emotional tone. Overall, the findings suggest that artificial intelligence can reliably evaluate the technical aesthetic features of gastronomic images, while researcher interpretation remains stronger in analyzing contextual and cultural layers. In this respect, the study offers an original methodological contribution by demonstrating the applicability of a researcher–AI hybrid analytical model in the fields of gastronomy and hospitality.

Keywords

• Gastronomic Images
• Artificial Intelligence
• Content Analysis
• Michelin Key
• Social Media

Gastronomik Görselli Sosyal Medya Paylaşımlarının Kıyaslamalı Analizi: Michelin Anahtarlı Oteller Örneği

Abstract

Sosyal medya platformlarında paylaşılan gastronomik görseller, konaklama işletmelerinin estetik sunumunu, marka imajını ve gastronomik deneyim algısını şekillendiren temel unsurlardan biri hâline gelmiştir. Bu çalışma, Türkiye’deki Michelin Anahtarlı otellerin sosyal medya paylaşımlarında yer alan gastronomi görsellerini MAXQDA yazılımı kullanılarak araştırmacı tarafından gerçekleştirilen nitel içerik analizi ve ChatGPT Vision ile gerçekleştirilen yapay zekâ destekli değerlendirme yaklaşımı doğrultusunda karşılaştırmalı olarak incelemektedir. Araştırma örneklemini, 26 otelin resmi Instagram hesaplarından seçilen toplam 252 gastronomik görsel oluşturmuştur. Görseller, renk estetiği, kompozisyon, aydınlatma, alan derinliği, profesyonellik, otantiklik, atmosfer, duygusal ton ve insan/el unsuru olmak üzere dokuz tematik kod doğrultusunda analiz edilmiştir. Veriler MAXQDA kullanılarak araştırmacı tarafından kodlanmış; aynı görseller ChatGPT Vision’a yüklenerek model tarafından üretilen betimsel yorumlar aynı tematik çerçevede nitel olarak karşılaştırılmıştır. Bulgular, kompozisyon, aydınlatma, profesyonellik ve renk estetiğinin hem araştırmacı kodlamasında hem de yapay zekâ değerlendirmelerinde en baskın estetik unsurlar olduğunu göstermektedir. Yapay zekânın teknik estetik bileşenlerde araştırmacı değerlendirmeleriyle yüksek düzeyde örtüşme gösterdiği; buna karşın atmosfer, kültürel temsil ve duygusal ton gibi daha soyut temalarda daha yüzeysel yorumlar sunduğu belirlenmiştir. Sonuçlar, yapay zekânın gastronomi görsellerinin teknik estetik unsurlarını tutarlı biçimde değerlendirebildiğini, ancak bağlamsal ve kültürel katmanların yorumlanmasında araştırmacı yorumunun hâlen daha güçlü olduğunu ortaya koymaktadır. Bu yönüyle çalışma, gastronomi ve konaklama alanında araştırmacı–yapay zekâ hibrit analiz modelinin uygulanabilirliğini gösteren özgün bir metodolojik katkı sunmaktadır.

Keywords

• Gastronomi Görselleri
• Yapay Zekâ
• İçerik Analizi
• Michelin Anahtarı
• Sosyal Medya

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