摘要
【目的/意义】通过对公共文化云平台中用户网上评论的采集,探讨用户对公共文化云平台运营的需求类型,根据需求特点不断优化公共文化活动提供方式以及内容形式,提高公共文化云平台中的服务质量。【方法/过程】通过网络爬虫技术采集公共文化云平台用户网上留言与线上评论,运用Keybert算法将评论中的关键词提取出来并进行文本编码,最终形成8个用户需求要素,根据该需求要素设计Kano问卷并展开调查,分别展开混合类分析、Kano模型归类以及Better-Worse系数分析,界定用户的需求类型。【结果/结论】研究发现积分奖励、文化特色以及宣传推广为魅力型需求,网站运营维护、资源获取为基本型需求,社团建设为期望型需求,网站预订效率以及活动形式为无差别需求。根据需求类型的不同对公共文化云平台改进方向提出相关建议,以支持公共文化云平台进一步改进和优化。【创新/局限】本文针对公共文化云平台的用户需求分析的工作有利于提升公共文化云平台的整体服务水平,但由于数据收集的不够全面,且样本量有限,其科学性有待进一步考察。
【Purpose/significance】Through the collection of users'online comments on the public culture cloud platform,this paper discusses the types of users'demands for the operation of the public culture cloud platform,constantly optimizes the ways and content forms of public cultural activities according to the characteristics of the demands,and improves the service quality of the public culture cloud platform.【Method/process】Collect online messages and online comments from users of public culture cloud platform by web crawler technology,extract keywords in comments by Keybert algorithm and carry out text coding,and finally form 8 user demand elements.According to these demand elements,Kano questionnaire is designed and investigated.Mixed class analysis,Kano model classification and Better-Worse coefficient analysis are carried out respectively to define the user's demand type.【Result/conclusion】The research found that points reward,cultural characteristics and publicity and promotion are attractive needs,website operation and maintenance,resource acquisition are basic needs,community construction is expected needs,website booking efficiency and activity forms are undifferentiated needs.According to different demand types,relevant suggestions are put forward for the improvement direction of the public culture cloud platform to support further improvement and optimization of the public culture cloud platform.【Innovation/limitation】The analysis of the user needs of the public culture cloud platform in this paper is conducive to improving the overall service level of the public culture cloud platform,but due to the incomplete data collection and limited sample size,its scientificity needs to be further investigated.
作者
何文瑾
王战平
谭春辉
HE Wenjin;WANG Zhanping;TAN Chunhui(National Cultural Industry Research Center,Central China Normal University,Wuhan 430079,China;School of Information Management,Central China Normal University,Wuhan 430079,China)
出处
《情报科学》
CSSCI
北大核心
2024年第8期184-192,共9页
Information Science
基金
国家社会科学基金一般项目“虚拟学术社区中科研人员合作机制研究”(18BTQ081)
