Prof.SHI Yang from SAFTI has recently published a paper titled “When Words Meet Visuals: How Content Composition Drives Social Media Engagement for Marketer-Generated Content”in the Journal of Marketing Research (JMR), a world-renowned academic journal in the field of marketing.
Journal of Marketing Research (JMR), established in 1964, is a premier international journal published by the American Marketing Association (AMA). It features high-quality empirical research and methodological innovations across various domains, including consumer behavior, advertising and communication, brand management, digital and social media, and market response models. Emphasizing the integration of academic rigor and practical relevance, JMR is widely recognized as one of the most influential journals in marketing. It is also included in the UTD 24 ranking list, a leading collection of journals used by the University of Texas at Dallas to evaluate the research productivity of business schools worldwide. This publication reflects the School’s commitment to high-quality scientific research and cross-disciplinary excellence.
Abstract of the paper: 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.(URL link:https://journals.sagepub.com/doi/abs/10.1177/00222437251373042)
Faculty Profiles:
SHI Yang, is a tenured associate professor at Shenzhen Audencia Financial Technology Institute, Shenzhen University. She holds a Ph.D.in marketing from Hong Kong University of Science and Technology. She has been a visiting assistant professor at the Hong Kong University of Science and Technology and assistant professor at Lingnan College, Sun Yat-sen University.
Professor SHI is dedicated to addressing marketing challenges through statistical and economic modeling. Her main research interests include quantitative marketing, advertising, media consumption, cross-screen marketing, influencer marketing, visual analytics, data mining, dynamic structural models, and financial marketing.
She has published multiple papers in leading international journals and has presided over several research grants, including those from the National Natural Science Foundation of China and the Guangdong Provincial Philosophy and Social Science Foundation.
Professor SHI has been recognized with numerous honors and awards, including the Shenzhen University Liyuan Outstanding Young Scholar Award, Top Ten Young Faculty Award, Excellent Class Advisor Award, and Outstanding Practice Teaching Supervisor Award.
