Instagram Reels Engagement Drivers: Machine Learning Insights into Celebrities and Brands

Öz

The paper explores the major motivators of user interaction on Instagram Reels, a rising short video form in digital marketing. Despite the central role played by Reels in content strategies, there is still minimal empirical research on which specific features are relevant in driving the engagement. To fill this gap, we analyzed 438 Instagram Reels of global celebrities and brands in the period from January to March 2024. A combination of exploratory data analysis with a Random Forest regression model was applied in a specific way so that it could estimate the importance of the features and find the most significant predictors of the engagement rate. These were the ranked features, which then were the input of a K-Means clustering analysis which indicated patterns of content that were linked to different degrees of audience response. The results indicate that celebrity and brand presence is the most influential factor (22.10% importance), followed by content type (19.03%), age representation (16.27%), and human activity (16.16%). In contrast to common assumptions, the findings show that neutral emotional tone generates the highest engagement, while positive tone yields the lowest, suggesting that authenticity and subtle emotional expression may be more effective than overt positivity in short-form video contexts. The combination of machine learning methods and traditional engagement theory within the study gives practical recommendations to the marketer and will create a clear, reproducible map of research on short-form video analytics in the future.

Anahtar Kelimeler

• Instagram Reels
• Digital marketing
• Engagement Rate
• Machine Learning
• Social Media Marketing

Etik Beyan

The study entitled “Instagram Reels Engagement Drivers: Machine Learning Insights into Celebrities and Brands” was conducted in accordance with scientific research principles, ethical standards, and citation guidelines. No manipulation, fabrication, or falsification was performed on the collected data. Furthermore, this study has not been submitted to any other academic publication venue for evaluation. Ethical committee approval was not required for this research. Statement of Contribution Rate of Researchers: The first author contributed 60%, and the second author contributed 40%. Declaration of Conflict: There are no potential conflicts of interest in this study. Funding: No funding was received from any institution or organization for this study. Statement of Use for Artificial Intelligence and Its Types: Artificial intelligence and its various types were not used in the writing of this article. Data Sharing Statement: We declare that, upon reasonable request for the purpose of verifying the findings, we can share the data of this study according to the conditions specified in the relevant section of the "ethical principles and publication policy". Notes: This article was presented as a poster at the European Academy of Marketing (EMAC) Spring Conference 2025, held in Pozuelo, Spain, from 27-30 May 2025.

Instagram Reels Etkileşimini Artıran Faktörler: Ünlüler ve Markalar Hakkında Makine Öğrenmesi İçgörüleri

Öz

Bu çalışma, dijital pazarlamada yükselen kısa video formatlarından biri olan Instagram Reels üzerinde kullanıcı etkileşimini yönlendiren temel faktörleri incelemektedir. Reels içerik stratejilerinde merkezi bir rol oynamasına rağmen, etkileşimi hangi spesifik özelliklerin yönlendirdiğine dair ampirik araştırmalar hâlen sınırlıdır. Bu boşluğu doldurmak amacıyla, Ocak–Mart 2024 döneminde küresel ölçekte tanınan ünlüler ve markalar tarafından paylaşılan 438 Instagram Reels içeriği analiz edilmiştir. Özelliklerin önemini tahmin edebilmek ve etkileşim oranının en güçlü belirleyicilerini ortaya koyabilmek için keşifsel veri analizi ile Random Forest regresyon modeli birlikte kullanılmıştır. Elde edilen özellik önem sıralamaları, farklı düzeylerde izleyici tepkisiyle ilişkilendirilen içerik örüntülerini belirlemek amacıyla K-Means kümeleme analizine girdi olarak kullanılmıştır. Sonuçlar, ünlü ve marka varlığının en etkili faktör olduğunu (%22,10 önem düzeyi), bunu içerik türü (%19,03), yaş temsili (%16,27) ve insan aktivitesi (%16,16) değişkenlerinin izlediğini göstermektedir. Yaygın varsayımların aksine, bulgular nötr duygusal tonun en yüksek etkileşimi sağladığını, olumlu tonun ise en düşük etkileşim düzeyine sahip olduğunu ortaya koymaktadır. Bu durum, kısa video bağlamında özgünlük ve daha örtük duygusal ifadenin, açık ve yoğun pozitiflikten daha etkili olabileceğini düşündürmektedir. Makine öğrenmesi yöntemlerinin geleneksel etkileşim teorileriyle birlikte kullanılması, pazarlamacılara yönelik pratik öneriler sunmakta ve gelecekte kısa video analitiği alanındaki araştırmalar için açık ve tekrarlanabilir bir çerçeve ortaya koymaktadır.

Anahtar Kelimeler

• Instagram Reels
• Dijital Pazarlama
• Etkileşim Oranı
• Makine Öğrenmesi
• Sosyal Medya Pazarlaması

Etik Beyan

“Instagram Reels Etkileşimini Artıran Faktörler: Ünlüler ve Markalar Hakkında Makine Öğrenmesi İçgörüleri” başlıklı çalışmanın yazım sürecinde bilimsel kurallara, etik ve alıntı kurallarına uyulmuş; toplanan veriler üzerinde herhangi bir tahrifat yapılmamış ve bu çalışma herhangi başka bir akademik yayın ortamına değerlendirme için gönderilmemiştir. Bu araştırma da etik kurul kararı zorunluluğu bulunmamaktadır. Araştırmacıların Katkı Oranı Beyanı: 1.yazar: % 60, ikinci yazar % 40 oranında katkı sağlamıştır. Çatışma Beyanı: Çalışmada herhangi bir potansiyel çıkar çatışması söz konusu değildir. Finansman: Bu çalışma için herhangi bir kurum veya kuruluştan destek alınmamıştır. Yapay Zeka ve Türleri Kullanım Beyanı: Bu makalenin yazımında yapay zeka ve türleri kullanılmamıştır. Veri Paylaşım Beyanı: Bu çalışmanın verilerini bulguların doğrulanması amacıyla makul bir talep üzerine “etik ilkeler ve yayın politikası”nın ilgili kısmında belirtilen şartlara göre paylaşabileceğimizi beyan ederiz. Not: Bu makale, 27-30 Mayıs 2025 tarihleri arasında İspanya'nın Pozuelo kentinde düzenlenen Avrupa Pazarlama Akademisi (EMAC) Bahar Konferansı 2025'te poster olarak sunulmuştur.

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