Research on the Optimized Creation and Talent Cultivation Mode of Online Micro Short Drama under the Background of Industry-Education Integration

Abstract

The ongoing evolution of the micro-short drama industry has led to increasingly sophisticated skill demands for professionals. In response, this study leverages the synergy between industry and education, employing Word2Vec and spectral clustering to develop a talent demand model predicated on text mining techniques for micro short dramas. A specialized talent demand dictionary was established to facilitate the analysis of job distribution characteristics and talent requirements within the micro short drama sector. This research introduces an optimized strategy for content creation and a novel approach to talent development for online micro skits. We conducted pedagogical experiments with students from four digital media classes across two academic levels at a university to assess the efficacy of this talent development model. The experiments specifically measured its impact on enhancing students’ abilities in micro skit creation. The results underscored interpersonal communication and content creation as the paramount skills in micro short drama, constituting 36.48% and 32.73% of talent demands, respectively. Post-experiment, the micro skit creation skills of students in the experimental cohort were observed to improve by 26.60% compared to their peers in standard classes and by 41.87% relative to their baseline capabilities prior to the experiment. These findings highlight the substantial benefits of the proposed talent cultivation model. The discussion in this paper addresses the refined strategies for creating and nurturing talent in networked micro short dramas, presenting a significant contribution to educational methodologies and scholarly discourse in digital media studies.

Keywords

• word2vec
• spectral clustering
• text mining
• teaching experiment
• micro short drama creation
• 68p30