Predicting social media engagement with computer vision: An examination of food marketing on Instagram
通过分析Instagram上餐厅食品图片的视觉特征，发现食物外观越典型（被AI识别越自信），获得的点赞和评论越多，因为典型食物更容易引发积极情绪和心理加工。
In a crowded social media marketplace, restaurants often try to stand out by showcasing elaborate “Instagrammable” foods. Using an image classification machine learning algorithm (Google Vision AI) on restaurants’ Instagram posts, this study analyzes how the visual characteristics of product offerings (i.e., their food) relate to social media engagement. Results demonstrate that food images that are more confidently evaluated by Google Vision AI (a proxy for food typicality) are positively associated with engagement (likes and comments). A follow-up experiment shows that exposure to typical-appearing foods elevates positive affect, suggesting they are easier to mentally process, which drives engagement. Therefore, contrary to conventional social media practices and food industry trends, the more typical a food appears, the more social media engagement it receives. Using Google Vision AI to identify what product offerings receive engagement presents an accessible method for marketers to understand their industry and inform their social media marketing strategies.