摘要
研究遵循“现象描述—问题发现与分析—实践改进”的逻辑,探究截至2024年底,我国副省级以上综合档案馆推出且更新完毕的档案微短剧的叙事问题与人工智能生成内容赋能其优化路径。第一阶段,人工智能解构档案微短剧作品,提取景别等八类结构化数据,借助统计软件进行频次统计与交叉分析,提炼档案微短剧叙事要素特征;第二阶段,结合扎根编码逻辑,微短剧叙事等理论,揭示档案微短剧叙事在时空、情感、场景、互动等叙事中的问题及原因;第三阶段,引入人工智能生成内容技术进行实践改进,为数字叙事下的档案微短剧叙事优化提供方法论参考。
The research follows the logic of“Phenomenon description--Problem discovery and analysis--Practice improvement”,exploring the 2024,the narrative problem and artificial intelligence generated content of the Archives micro-dramas launched and updated by the comprehensive Archives above the deputy provincial level in our country enable its optimal path.In the first stage,AI deconstructs archival miniseries,extracts 8 types of structured data such as landscape,and carries out frequency statistics and cross-analysis with SPSSAU to refine the characteristics of narrative elements of archival miniseries,combined with grounded coding logic,micro-drama narrative and other theories,this paper reveals the problems and causes of archival micro-drama narrative in time and space narrative,emotional narrative,scene narrative and interactive narrative,the introduction of AIGC technology for practical improvement provides a methodological reference for the narrative optimization of AIGC Archives miniseries under digital narrative.
作者
郑慧
李袁
Zheng Hui;Li Yuan
出处
《档案管理》
北大核心
2025年第5期56-62,共7页
Archives Management
基金
2024年广西民族大学研究生教育创新计划项目“数字叙事视角下档案微短剧开发研究”(项目编号:gxmzu-chxs2024281)的阶段性研究成果。
关键词
数字叙事
时空叙事
档案
微短剧
人工智能
人工智能生成内容
沉浸式
角色体验
Digital Narrative
Spatio-temporal Narrative
Archives
Micro-drama
Artificial Intelligence
AI-generated Content
Immersive
Role Experience
