Audience in the Loop: Viewer Feedback-Driven Content Creation in Micro-drama Production on Social Media

Paper Title

Audience in the Loop: Viewer Feedback-Driven Content Creation in Micro-drama Production on Social Media

Publication Info

• Topic area: Feedback-driven narrative production in micro-drama ecosystems on social media platforms.
• Keywords: Micro-drama, social media, audience feedback, participatory culture, platform algorithms, creative labor, storytelling, iterative production, digital content, AI-assisted creation.

Background and Problem

• Problem / challenge: Existing research focuses on platform affordances and writer experiences but lacks a systematic understanding of how audience feedback shapes micro-drama production workflows and narrative structures.
• Significance: Micro-dramas are a rapidly growing narrative form, especially in Chinese markets, with significant cultural and economic impact. Understanding feedback-driven production can improve platform design and creative practices.
• Motivation and related work: Prior studies have explored participatory media, algorithmic governance, and digital storytelling, but they often overlook how audience feedback is interpreted and integrated into iterative creative processes. This study addresses this gap by examining the triadic interaction between writers, audiences, and platforms.

Solution

• Proposed approach: A qualitative study using semi-structured interviews with 28 micro-drama creators to investigate feedback-driven production workflows and audience interaction mechanisms.
• Novelty:
  1. Identifies how audience feedback reshapes narrative production through iterative, platform-mediated processes.
  2. Highlights the emergence of new roles and workflows in micro-drama production, such as multifunctional creators and data-driven decision-making.
  3. Explores the role of AI tools and platform algorithms in shaping creative practices and audience engagement.
• Procedure and key techniques:
  • Conducted semi-structured interviews with micro-drama creators, including screenwriters, directors, and producers.
  • Analyzed how creators collect, interpret, and integrate audience feedback into narrative decisions.
  • Examined the influence of platform algorithms and data analytics on production workflows.

Results

• Concrete findings:
  • Audience feedback, such as comments, memes, and reposts, significantly influences plot direction, character development, and pacing.
  • Two main production models were identified: situational micro-dramas with real-time feedback integration and platform-commissioned productions with systematic data analysis.
  • AI tools are increasingly used for audience sentiment analysis and creative ideation but face limitations in interpreting nuanced feedback.
• Advantage over baselines:
  • Demonstrates how feedback-driven production differs from traditional screenwriting by emphasizing rapid iteration, audience co-creation, and platform-mediated constraints.
  • Highlights the unique role of micro-dramas as a hybrid form combining serialized storytelling with short-form video dynamics.
• Experiments / evaluation:
  • Data collected through interviews with 28 participants, including creators with diverse roles and experiences across platforms like Douyin, TikTok, and Tencent.
  • Thematic analysis of interview transcripts to identify patterns in feedback integration and creative workflows.
• Limitations and future work:
  • Self-reported data may introduce bias; findings are not validated against large-scale content analysis.
  • Limited focus on audience perspectives and cross-cultural comparisons.
  • Future research should integrate computational methods and expand cross-regional studies.

Summary

This study investigates how audience feedback drives the iterative production of micro-dramas on social media platforms, revealing a new paradigm of collaborative storytelling. By analyzing interviews with 28 creators, the research highlights the central role of platform algorithms and audience signals in shaping narrative decisions, production workflows, and creative roles. The findings emphasize the potential of AI tools and configurable feedback systems to enhance creative autonomy while addressing challenges like narrative homogenization and data-driven constraints. This work contributes to understanding feedback-driven storytelling and offers design implications for more inclusive and sustainable creative ecosystems.