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AIGC产品用户需求特征体系构建及改进策略研究

Research on the Construction of User Demand Characteristic System and Improvement Strategy of AIGC Products
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摘要 [目的/意义]从用户视角出发,探索AIGC产品的用户需求及特征,为国产AIGC产品质量的提升提供参考和建议,从而推动我国AIGC行业的高水平发展。[方法/过程]以ChatGPT和文心一言为研究对象,爬取微博、知乎、抖音、百度贴吧4个社交媒体平台的116046条评论文本,通过BERTopic主题模型提取用户关注主题,构建AIGC产品的用户需求特征体系,基于IPA分析工具从主题关注度和满意度两个维度分析国内外AIGC产品的需求特征差异,据此提出我国AIGC产品的改进策略。[结果/结论]AIGC产品的用户需求主要分为可获得性、可靠性、体验性、创新性、功能性、理解性、趣味性、安全性8类;我国AIGC产品的改进策略包括提升内容可靠性、增强文化适配度、完善安全保障体系、助推核心技术创新。 [Purpose/Significance]This paper aims to explore the user demand and characteristics of AIGC products from the perspective of user,providing reference and suggestions for the improvement of AIGC products quality,and promoting the high-level development of AIGC industry.[Method/Process]Taking ChatGPT and Wenxin as the research objects,this paper crawled 116046 comment text from four social media platforms,including Weibo,Zhihu,Douyin and Baidu Tieba,then used BERTopic to extract the users’focus topics and constructed a user demand characteristic system of AIGC products.Based on the IPA analysis tool,it analyzed the differences in demand characteristics of AIGC products at home and abroad from both attention and satisfaction dimensions,and it proposed the improvement strategy of AIGC products in China.[Result/Conclusion]The user demand of AIGC products are mainly divided into eight categories:availability,reliability,experience,innovation,functionality,understanding,interest and security.The improvement strategy for AIGC products in China includes improving the reliability of content,enhancing cultural adaptability,improving the security system,and boosting core technology innovation.
作者 毕达天 王璐 王雨菲 车尧 Bi Datian;Wang Lu;Wang Yufei;Che Yao(School of Business and Management,Jilin University,Changchun 130012;Institute of Scientific and Technical Information of China,Beijing 100038)
出处 《图书情报工作》 北大核心 2024年第14期14-24,共11页 Library and Information Service
基金 国家社会科学基金项目“基于用户跨社交媒体的信息行为偏好特征挖掘与推荐”(项目编号:21BTQ059)研究成果之一。
关键词 AIGC 需求特征体系 主题挖掘 BERTopic模型 IPA分析 AIGC demand characteristic system topic mining BERTopic model IPA analysis
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