When Words Meet Visuals: How Content Composition Drives Social Media Engagement for Marketer-Generated Content
主讲人: 党矗,香港大学商学院 助理教授
主持人: 殷云露,复旦大学管理学院 副教授
时间:2026年4月21日(周二)下午13:00-15:00
地点:思源教授楼624室
Abstract:How does the balance between text and pictorial content in marketer-generated social media posts affect user engagement? The authors address this question by using computer vision and natural language processing tools to extract the visual and textual features of 34,610 organic brand posts from Facebook and Instagram. Using a Confounding-and-Cluster-Robust Causal Forests model, they test how the balance of text and picture affects social media engagement across content and visual contexts. Results show that posts with greater emphasis on overlay text over pictorial content tend to have fewer likes and comments. However, the performance of text-oriented posts improves if text is more centered, informative, emotionally positive, and congruent with the pictorial content, and if the picture contains fewer prominent objects or less information such as social cues. They quantify how incremental changes in such content composition affect social media engagement. These findings set forth evidence-based principles for optimizing text and picture balance in marketer-generated content (MGC) and provide actionable guidelines on whether, where, when, and how to present text on an image. This research highlights the potential for transforming content and media creation from an imprecise art form into an empirical science nested within a data-driven visual optimization framework.
Bio:党矗(Ivy Chu Dang)是香港大学商学院市场营销学助理教授。她的主要研究兴趣涵盖量化营销中的信息经济学以及社交媒体营销。她研究消费者如何搜寻信息及其对购买决策的影响,还探讨企业如何制定有效的信息策略。在社交媒体领域,她关注用户(UGC)、商家(MGC)以及人工智能生成内容(AIGC)的影响力,同时也研究网红营销中的前沿趋势。她的研究成果发表在Marketing Science,Journal of Marketing Research,Information Systems Research 和Quantitative Marketing and Economics等顶级期刊。
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