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Brands and enterprises have increasingly relied on user engagement with social media content for product promotion; however, research on how social media posts effectively capture user attention remains limited. The present study addresses this gap by examining the influence of visual complexity and textual emotional tone—used as independent variables in this analysis—on consumer engagement (measured through likes, comments, saves, and shares) across different combinations. The findings indicate that both factors significantly affect engagement, with posts characterized by high visual complexity and a positive emotional tone yielding particularly strong outcomes. Data collected through simulated questionnaire surveys (N = 740 valid responses after excluding incomplete or biased data) and actual content published on the RedNote (also known as Xiaohongshu) platform consistently support the study’s two core hypotheses. Grounded in Media Richness Theory (MRT), the Elaboration Likelihood Model (ELM), and Dual Process Theories (DPT), this research extends the existing literature by elucidating the synergistic effects of visual and emotional elements in user-generated content (UGC). These results provide actionable insights for marketers, content creators, and platform designers seeking to optimize social media content strategies.

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Impacts of Content Emotions and Visuals on Brand Communication

  • 会议论文

  • 发表日期：

    2026年

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  • Yijia Chen,
  • Yingpeng Zhu,
  • Matthew Tingchi Liu,
  • Edmund H. N. Loi

摘要

Brands and enterprises have increasingly relied on user engagement with social media content for product promotion; however, research on how social media posts effectively capture user attention remains limited. The present study addresses this gap by examining the influence of visual complexity and textual emotional tone—used as independent variables in this analysis—on consumer engagement (measured through likes, comments, saves, and shares) across different combinations. The findings indicate that both factors significantly affect engagement, with posts characterized by high visual complexity and a positive emotional tone yielding particularly strong outcomes. Data collected through simulated questionnaire surveys (N = 740 valid responses after excluding incomplete or biased data) and actual content published on the RedNote (also known as Xiaohongshu) platform consistently support the study’s two core hypotheses. Grounded in Media Richness Theory (MRT), the Elaboration Likelihood Model (ELM), and Dual Process Theories (DPT), this research extends the existing literature by elucidating the synergistic effects of visual and emotional elements in user-generated content (UGC). These results provide actionable insights for marketers, content creators, and platform designers seeking to optimize social media content strategies.