Dijital Gıda Güvenliği Savunuculuğunda Tüketici Tepki Örüntüleri: Instagram Yorumları Üzerine Betimsel Bir Analiz

Öz

Bu çalışma, Türkiye'deki bir dijital gıda güvenliği savunuculuk hesabının Ocak–Ağustos 2025 döneminde yayımladığı 76 kısa video ile 40.987 kullanıcı yorumunu betimsel ve keşifsel bir yaklaşımla incelemektedir. Araştırma; hangi içerik türlerinin tüketici söylemini yoğunlaştırdığını, çerçeveleme biçimlerinin etkileşim örüntülerini nasıl şekillendirdiğini ve marka düzeyinde güvensizliğin nasıl örgütlendiğini ortaya koymaktadır. Bulgular, tüketici etkileşiminin nesnel sağlık riski düzeyiyle örtüşmediğini; gıda zehirlenmesi içeriklerinin en düşük etkileşimi üretirken fiyat adaletsizliği ve boykot içeriklerinin en yüksek etkileşimi ürettiğini göstermektedir. Kesirli Tepki Modeli analizi, aktivizm çerçevelemesinin (V4), korku-dehşet yoğunluğunun (V1) ve bilgi-sinyal türünün (V3) yorum/beğeni oranı üzerinde istatistiksel olarak anlamlı olumsuz etkiler ürettiğini; en güçlü yordayıcının ise aktivizm çerçevelemesi olduğunu ortaya koymaktadır. Marka analizi, güvensizliğin fiyat, katkı maddesi ve etiket yanıltmacası boyutlarını kapsayan çok boyutlu bir yapı sergileyebileceğine işaret etmekte; ancak bu örüntünün nedensel değil betimsel bir bulgu olarak değerlendirilmesi gerektiği vurgulanmaktadır. Bulgular, Korku-Yeterlilik İşleme Modeli ve soyut-kişilerarası güven ayrımı çerçevesinde tartışılmakta; ekonomik haksızlık algısı ile kurumsal hesap verebilirlik talebinin Türk tüketicilerinin dijital gıda güvenliği söyleminde belirleyici bir rol oynadığı ileri sürülmektedir.

Anahtar Kelimeler

• Gıda güvenliği risk algısı
• tüketici söylemi
• sosyal medya savunuculuğu
• içerik analizi
• çerçeveleme
• kesirli tepki modeli
• kurumsal güven.

Destekleyen Kurum

Herhangi bir kurumdan destek alınmamıştır.

Etik Beyan

Bu araştırma, sosyal medya platformunda kamuya açık biçimde yayımlanmış içeriklerin ikincil analizini kapsamaktadır. Türkiye Kişisel Verilerin Korunması Kanunu'nun (KVKK, 6698 sayılı Kanun) 28. maddesi uyarınca kamuya açık verilerin bilimsel amaçla işlenmesi, ilgili kişilerin açık rızası aranmaksızın gerçekleştirilebilmekte; bu hüküm, veri işlemenin temel hak ve özgürlüklere zarar vermemesi ve araştırmanın meşru bir bilimsel amaca dayanması koşuluna bağlıdır. Söz konusu çalışmada her iki koşul da sağlanmaktadır. Bu gerekçelerle çalışma, etik kurul onayı gerektiren bir araştırma kapsamına girmemektedir. Bununla birlikte araştırmacı, marka ve kurum adlarını anonimleştirme yoluna başvurmuştur. Araştırma kapsamında adı geçen tüm marka, zincir market ve işletme isimleri kodlanarak anonimleştirilmiştir. Bu önlemler aracılığıyla bireysel/kurumsal kimliklerin ifşa edilmesi önlenmiş; araştırma süreci boyunca kişisel veri güvenliğine azami özen gösterilmiştir.

Consumer Response Patterns in Digital Food Safety Advocacy: A Descriptive Analysis of Instagram Comments

Öz

This study examines, through a descriptive and exploratory approach, 76 short videos published by a digital food safety advocacy account in Turkey between January and August 2025, along with 40,987 user comments. The research reveals which content types intensify consumer discourse, how framing strategies shape engagement patterns, and how brand-level distrust is structured. Findings indicate that consumer engagement does not correspond to objective health risk levels; while food poisoning content generates the lowest engagement, price injustice and boycott content generates the highest. Fractional Response Model analysis reveals that activism framing (V4), dread intensity (V1), and information-signal type (V3) each have statistically significant negative effects on the comment-to-like ratio, with activism framing emerging as the strongest predictor. Brand analysis suggests that distrust may exhibit a multidimensional structure..., though this pattern should be interpreted as descriptive rather than causal. Findings are discussed within the framework of the Dread-Efficacy Processing Model and the abstract-interpersonal trust distinction, suggesting that perceived economic injustice and demand for institutional accountability play a determining role in Turkish consumers' digital food safety discourse.

Anahtar Kelimeler

• Food safety risk perception
• consumer discourse
• social media advocacy
• content analysis
• framing
• fractional response model
• institutional trust.

Destekleyen Kurum

No financial or institutional support was received from any organization.

Etik Beyan

This research encompasses the secondary analysis of publicly available content published on social media platforms. Pursuant to Article 28 of the Turkish Personal Data Protection Law (KVKK, Law No. 6698), the processing of publicly available data for scientific purposes may be carried out without seeking the explicit consent of the relevant individuals, provided that the processing does not harm fundamental rights and freedoms and that the research is based on a legitimate scientific purpose. Both conditions are satisfied in the present study. For these reasons, this study does not fall within the scope of research requiring ethics committee approval. Nonetheless, the researcher has employed anonymization procedures for brand and institutional names. All brand, chain store, and business names referenced within the scope of the research have been coded and anonymized. Through these measures, the disclosure of individual and corporate identities has been prevented, and utmost care has been taken to ensure personal data security throughout the research process.

Kaynakça

1. Almaghrabi, M. A. (2023). Assessing public interest, risk perceptions, and awareness of food safety in Saudi Arabia: A cross-sectional study. Food Control, 151, 109810. https://doi.org/10.1016/j.foodcont.2023.109810
2. Assis, M. T. Q. M., Lucas, M. R., & Rainho, M. J. M. (2022). A meta-analysis on the trust in agrifood supply chains. Food Frontiers, 3, 413–427. https://doi.org/10.1002/fft2.137
3. Baba, F. V., & Esfandiari, Z. (2023). Theoretical and practical aspects of risk communication in food safety: A review study. Heliyon, 9(7), e18141. https://doi.org/10.1016/j.heliyon.2023.e18141
4. Beyaz Özbey, İ. (2022). Dijitalleşme, sosyal medya ve risk toplumu (Digitalization, social media and risk society). İmgelem, 6(10), 141–158. https://doi.org/10.53791/imgelem.1053815
5. Chamhuri, N., & Batt, P. J. (2015). Consumer perceptions of food quality in Malaysia. British Food Journal, 117(3), 1168–1187. https://doi.org/10.1108/BFJ-08-2013-0235
6. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum.
7. Danner, H., & Menapace, L. (2020). Using online comments to explore consumer beliefs regarding organic food in German-speaking countries and the United States. Food Quality and Preference, 83, 103912. https://doi.org/10.1016/j.foodqual.2020.103912
8. Djekic, I., Nikolic, A., Mujcinovic, A., Blazic, M., Herljevic, D., Goel, G., Trafiałek, J., Czarniecka-Skubina, E., Guiné, R., Gonçalves, J. C., Smole-Mozina, S., Kunčič, A., Miloradovic, Z., Miocinovic, J., Aleksic, B., Gomez-López, V. M., Osés, S. M., Ozilgen, S., & Smigic, N. (2022). How do consumers perceive food safety risks? Results from a multi-country survey. Food Control, 142, 109216. https://doi.org/10.1016/j.foodcont.2022.109216

9. Erkmen, Ö., & Sargın Can, B. (2022). Türkiye'de sosyal medyanın gıda aktivizmi amaçlı kullanımı: Gıdadedektifi örneğinin incelenmesi (The use of social media for food activism in Turkey: The case of Gıdadedektifi). Ege Üniversitesi İletişim Fakültesi Yeni Düşünceler Hakemli E-Dergisi, (17), 28–47. https://doi.org/10.56118/euifydhed.1113269
10. Faour-Klingbeil, D., Osaili, T. M., Al-Nabulsi, A. A., Jemni, M., & Todd, E. C. D. (2021). The public perception of food and non-food related risks of infection and trust in the risk communication during COVID-19 crisis: A study on selected countries from the Arab region. Food Control, 121, 107617. https://doi.org/10.1016/j.foodcont.2020.107617
11. Feldmann, C., & Hamm, U. (2015). Consumers' perceptions and preferences for local food: A review. Food Quality and Preference, 40, 152–164. https://doi.org/10.1016/j.foodqual.2014.09.014
12. Focker, M., van Asselt, E. D., Berendsen, B. J. A., van de Schans, M. G. M., van Leeuwen, S. P. J., Visser, S. M., & van der Fels-Klerx, H. J. (2022). Review of food safety hazards in circular food systems in Europe. Food Research International, 158, 111505. https://doi.org/10.1016/j.foodres.2022.111505
13. Franc-Dąbrowska, J., Ozimek, I., Pomianek, I., & Rakowska, J. (2021). Young consumers' perception of food safety and their trust in official food control agencies. British Food Journal, 123(8), 2693–2704. https://doi.org/10.1108/BFJ-11-2020-0992
14. Hilaire, J., Tindale, S., Jones, G., Pingarrón-Cárdenas, G., Bačnik, K., Ojo, M., & Frewer, L. J. (2022). Risk perception associated with an emerging agri-food risk in Europe: Plant viruses in agriculture. Agriculture & Food Security, 11, 21. https://doi.org/10.1186/s40066-022-00366-5
15. James, H. S., Segovia, M., & Giwa-Daramola, D. (2023). Food safety and cognitive biases: What we know, what we need to know, and why. British Food Journal, 125(10), 3717–3733. https://doi.org/10.1108/BFJ-09-2022-0824
16. Kasza, G., Csenki, E., Szakos, D., & Izsó, T. (2022). The evolution of food safety risk communication: Models and trends in the past and the future. Food Control, 138, 109025. https://doi.org/10.1016/j.foodcont.2022.109025
17. Kavruk, M., Balcı, T. N., Özel, İ. Ç., Ozalp, V. C., & Aydın, A. (2025). Global insights into food fraud from location-based analysis: Food adulteration in Turkey. Journal of the Science of Food and Agriculture, 105(11), 5833–5839. https://doi.org/10.1002/jsfa.14302
18. Kerby, D. S. (2014). The simple difference formula: An approach to teaching nonparametric correlation. Comprehensive Psychology, 3, 11.IT.3.1. https://doi.org/10.2466/11.IT.3.1
19. Krippendorff, K. (2004). Content analysis: An introduction to its methodology (2nd ed.). Sage.
20. Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174. https://doi.org/10.2307/2529310
21. Li, Y., & Zhao, M. (2025). How the product-harm crisis influences consumer boycotts: The role of social distance. Humanities and Social Sciences Communications, 12(1), 759. https://doi.org/10.1057/s41599-025-05058-6
22. Meijer, G. W., Lähteenmäki, L., Stadler, R. H., & Weiss, J. (2021). Issues surrounding consumer trust and acceptance of existing and emerging food processing technologies. Critical Reviews in Food Science and Nutrition, 61(1), 97–115. https://doi.org/10.1080/10408398.2020.1718597
23. Nygård, B., & Storstad, O. (1998). De-globalisation of food markets? Consumer perceptions of safe food: The case of Norway. Sociologia Ruralis, 38(1), 35–53. https://doi.org/10.1111/1467-9523.00062
24. Ozili, P. K. (2023). The acceptable R-square in empirical modelling for social science research. In C. Saliya (Ed.), Social research methodology and publishing results: A guide to non-native English speakers (pp. 134–143). IGI Global Scientific Publishing. https://doi.org/10.4018/978-1-6684-6859-3.ch009
25. Papke, L. E., & Wooldridge, J. M. (1996). Econometric methods for fractional response variables with an application to 401(K) plan participation rates. Journal of Applied Econometrics, 11(6), 619–632. https://doi.org/10.1002/(SICI)1099-1255(199611)11:6<619::AID-JAE418>3.0.CO;2-1
26. Pareti, M., Guo, J., Abudurofu, N., Liu, Q., Bulibuli, A., & Canavari, M. (2025). The impact of trust on Chinese consumers' acceptance of meat substitutes: The mediating role of perceived benefits and perceived risks, and the moderating role of consumer knowledge. Foods, 14(4), 669. https://doi.org/10.3390/foods14040669
27. Sadiq, M., Adil, M., & Paul, J. (2022). Organic food consumption and contextual factors: An attitude–behavior–context perspective. Business Strategy and the Environment, 32(6), 3383–3397. https://doi.org/10.1002/bse.3306
28. Siegrist, M. (2021). Trust and risk perception: A critical review of the literature. Risk Analysis, 41(3), 480–490. https://doi.org/10.1111/risa.13325
29. Siegrist, M., Luchsinger, L., & Bearth, A. (2021). The impact of trust and risk perception on the acceptance of measures to reduce COVID-19 cases. Risk Analysis, 41(5), 787–800. https://doi.org/10.1111/risa.13675
30. Simoglou, K. B., & Roditakis, E. (2022). Consumers' benefit–risk perception on pesticides and food safety: A survey in Greece. Agriculture, 12, 192. https://doi.org/10.3390/agriculture12020192
31. Slovic, P. (1987). Perception of risk. Science, 236(4799), 280–285. https://doi.org/10.1126/science.3563507
32. Suhaimi, A., Othman, A. A., Ghazali, A. F., & Sundram, V. P. K. (2024). The effect of trust in food safety, perception, product features and consumers' characteristics on consumers' purchase decision for safe food: A systematic literature review. Pertanika Journal of Social Sciences & Humanities, 32(2), 583–603. https://doi.org/10.47836/pjssh.32.2.11
33. Swani, K., & Labrecque, L. I. (2020). Like, comment, or share? Self-presentation vs. brand relationships as drivers of social media engagement choices. Marketing Letters, 31(2-3). https://doi.org/10.1007/s11002-020-09518-8
34. Tiozzo, B., Ruzza, M., Rizzoli, V., D'Este, L., Giaretta, M., & Ravarotto, L. (2020). Biological, chemical, and nutritional food risks and food safety issues from Italian online information sources: Web monitoring, content analysis, and data visualization. Journal of Medical Internet Research, 22(12), e23438. https://doi.org/10.2196/23438
35. Thomas, M. S., & Feng, Y. (2021). Consumer risk perception and trusted sources of food safety information during the COVID-19 pandemic. Food Control, 130, 108279. https://doi.org/10.1016/j.foodcont.2021.108279
36. Truong, V. A., Conroy, D. M., & Lang, B. (2021). The trust paradox in food labelling: An exploration of consumers' perceptions of certified vegetables. Food Quality and Preference, 93, 104280. https://doi.org/10.1016/j.foodqual.2021.104280
37. Usman, H., Projo, N. W. K., Chairy, C., & Haque, M. G. (2024). The role of trust and perceived risk on Muslim behavior in buying halal-certified food. Journal of Islamic Marketing, 15(7), 1902–1921. https://doi.org/10.1108/JIMA-09-2021-0303
38. Wu, W., Zhang, A., van Klinken, R. D., Schrobback, P., & Muller, J. M. (2021). Consumer trust in food and the food system: A critical review. Foods, 10(10), 2490. https://doi.org/10.3390/foods10102490
39. Yeasmin, D., Baker, M., Kamal, A. H. M., Islam, M. S., Rahman, M., Winch, P. J., & Unicomb, L. (2023). Exploring customers' perceptions of food adulteration at bazaars and supermarkets in Dhaka, Bangladesh; a qualitative exploration. BMC Public Health, 23(1), 206. https://doi.org/10.1186/s12889-022-14933-9
40. Ze, Y., van Asselt, E. D., Focker, M., & van der Fels-Klerx, H. J. (2024). Risk factors affecting the food safety risk in food business operations for risk-based inspection: A systematic review. Comprehensive Reviews in Food Science and Food Safety, 23, e13403. https://doi.org/10.1111/1541-4337.13403
41. Zhang, J., Wu, H.-C., Chen, L., & Su, Y. (2022). Effect of social media use on food safety risk perception through risk characteristics: Exploring a moderated mediation model among people with different levels of science literacy. Frontiers in Psychology, 13, 963863. https://doi.org/10.3389/fpsyg.2022.963863