基于用户生成内容的文创产品设计方法研究

徐正雯; 刘键; 刘佳昂; 李孟楠

doi:10.19554/j.cnki.1001-3563.2026.04.020

PDF(4299 KB)

包装工程（设计栏目） ›› 2026, Vol. 47 ›› Issue (4) : 231-243. DOI: 10.19554/j.cnki.1001-3563.2026.04.020

工业设计

基于用户生成内容的文创产品设计方法研究

徐正雯¹, 刘键^1,*, 刘佳昂², 李孟楠¹

作者信息 +

Design Methodology of Cultural and Creative Products Based on User-Generated Content

XU Zhengwen¹, LIU Jian^1,*, LIU Jia'ang², LI Mengnan¹

Author information +

文章历史 +

摘要

目的提出一套基于LDA主题模型的文创产品设计方法,提高文创产品的创新性与设计效率,并从全系统的角度为文创产品行业的产业链整合提供理论依据。方法以筛选出的50件故宫在售文创为样本,通过Python编程爬取用户购后的在线评论,利用相似度算法进行评论数据扩充,随后LDA主题模型对处理后的评论数据进行训练,结合困惑度及一致性曲线确定主题数为6,根据主题下的高频词人工归纳出主题,并将主题作为指标纳入文创产品设计方法。结论研究基于LDA主题模型训练,确定并归纳CMF设计、产品包装、文化内涵、产品类别、销售机制、产品服务6个主题,分析6个主题下现有文创产品设计的不足,产出有效的文创产品设计方法。

Abstract

The work aims to propose a cultural and creative product design methodology based on the LDA topic model to enhance the innovation and design efficiency of such products while providing theoretical support for the integration of the cultural and creative industry chain from a systemic perspective. With 50 cultural and creative products sold by the Palace Museum as samples, online reviews from users were collected via Python programming. A similarity algorithm was employed to expand the review dataset, which was then processed and trained with the LDA topic model. The number of topics was determined to be six based on perplexity and coherence curves. High-frequency words under each topic were manually summarized into themes, which were subsequently incorporated as indicators into the proposed cultural and creative product design methodology. Through the LDA topic model training, six themes are identified and summarized: CMF design, product packaging, cultural connotation, product categories, sales mechanisms, and product services. The deficiencies in the design of existing cultural and creative products under these six themes are analyzed and an effective design methodology is developed for cultural and creative products.

导出引用1

徐正雯, 刘键, 刘佳昂, 李孟楠. 基于用户生成内容的文创产品设计方法研究[J]. 包装工程. 2026, 47(4): 231-243 https://doi.org/10.19554/j.cnki.1001-3563.2026.04.020

XU Zhengwen, LIU Jian, LIU Jia'ang, LI Mengnan. Design Methodology of Cultural and Creative Products Based on User-Generated Content[J]. Packaging Engineering. 2026, 47(4): 231-243 https://doi.org/10.19554/j.cnki.1001-3563.2026.04.020

中图分类号： TB472

参考文献

[1] 牛富杰. 文创产品设计与开发研究[J]. 包装工程, 2023, 44(18): 400-403.
NIU F J.Design and Development of Cultural and Creative Products[J]. Packaging Engineering, 2023, 44(18): 400-403.
[2] 刘益.抓住文化产业高质量发展的着力点[N].人民日报,2024-07-17(9).
LIU Y. Seizing the Focus of High-Quality Development in the Cultural Industry[N].People's Daily, 2024-07-17(9).
[3] 张振鹏. 中国式现代化的文化产业高质量发展向度[J]. 深圳大学学报(人文社会科学版), 2023, 40(5): 47-56.
ZHANG Z P.High Quality Development Direction of Cultural Industries in the Process of Chinese Path to Modernization[J]. Journal of Shenzhen University (Humanities & Social Sciences), 2023, 40(5): 47-56.
[4] BURGESS S, SELLITTO C, COX C, et al.User-Generated Content (UGC) in Tourism: Benefits and Concerns of Online Consumers[C]// ECIS. 2009: 417-429.
BURGESS S, SELLITTO C, COX C, et al.User-Generated Content (UGC) in Tourism: Benefits and Concerns of Online Consumers[C]// Proceedings of the 17th European Conference on Information Systems (ECIS 2009). Verona, Italy: University of Verona, 2009: 417-429.
[5] 陈隽柏, 吴国平, 张童, 等. 语言学视角下人工智能生成内容与用户生成内容的对比研究——以在线医疗服务场景为例[J]. 情报理论与实践, 2024, 47(9): 192-201.
CHEN J B, WU G P, ZHANG T, et al.Comparative Study of Artificial Intelligence Generated Content and User Generated Content from a Linguistic Perspective: Taking Online Healthcare Services as an Example[J]. Information Studies (Theory & Application), 2024, 47(9): 192-201.
[6] BAHTAR A Z, MUDA M.The Impact of User - Generated Content (UGC) on Product Reviews towards Online Purchasing - a Conceptual Framework[J]. Procedia Economics and Finance, 2016, 37: 337-342.
[7] 钱升华, 邵波. 基于用户生成内容的大运河博物馆形象感知研究[J]. 中国博物馆, 2021(4): 67-73.
QIAN S H, SHAO B.Research on Image Perception and Quality Improvement of the Grand Canal Museum Based on UGC[J]. Chinese Museum, 2021(4): 67-73.
[8] 李贺, 张世颖. 移动互联网用户生成内容质量评价体系研究[J]. 情报理论与实践, 2015, 38(10): 6-11.
LI H, ZHANG S Y.Research on Quality Evaluation System of Mobile Internet User Generated Content[J]. Information Studies (Theory & Application), 2015, 38(10): 6-11.
[9] SUROWIECKI J.The Wisdom of Crowds[M]. New York: Doubleday, 2004.
[10] 施文, 渠玉杰, 王小双. 考虑文本结构特征的产品召回监督主题模型及应用研究[J]. 中国管理科学, 2026, 34(2): 103-119.
SHI W, QU Y J, WANG X S.Supervised Topic Modeling and Application Research on Product Recall Considering Textual Structural Features[J]. Chinese Journal of Management Science, 2026, 34(2): 103-119.
[11] 董同强, 朱彦君, 马秀峰. 基于中文文本类别信息的主题生成模型构建研究[J]. 情报科学, 2024, 42(4): 36-42.
DONG T Q, ZHU Y J, MA X F.Constructing a Topic Generation Model Based on Chinese Text Category Information[J]. Information Science, 2024, 42(4): 36-42.
[12] CHEN Y H, LI S F.Using Latent Dirichlet Allocation to Improve Text Classification Performance of Support Vector Machine[C]// 2016 IEEE Congress on Evolutionary Computation (CEC). Vancouver: IEEE, 2016: 1280-1286.
[13] 王孟, 苏进城, 陈志德. 基于LDA和Word2Vec模型的学位论文评阅意见主题挖掘与分析[J]. 福建师范大学学报(自然科学版), 2024, 40(5): 41-51.
WANG M, SU J C, CHEN Z D.Mining and Analysis of Thesis Review Topics Based on LDA and Word2Vec Models[J]. Journal of Fujian Normal University (Natural Science Edition), 2024, 40(5): 41-51.
[14] 李帅, 于娟, 巫邵诚. 基于集成学习的跨语言文本主题发现方法研究[J]. 计算机科学, 2024, 51(S1): 182-189.
LI S, YU J, WU S C.Cross-Lingual Text Topic Discovery Based on Ensemble Learning[J]. Computer Science, 2024, 51(S1): 182-189.
[15] BASTANI K, NAMAVARI H, SHAFFER J. Latent Dirichlet Allocation (LDA) for Topic Modeling of the CFPB Consumer Complaints[J]. Expert Systems with Applications, 2019, 127: 256-271.
[16] 夏立新, 曾杰妍, 毕崇武, 等. 基于LDA主题模型的用户兴趣层级演化研究[J]. 数据分析与知识发现, 2019, 3(7): 1-13.
XIA L X, ZENG J Y, BI C W, et al.Identifying Hierarchy Evolution of User Interests with LDA Topic Model[J]. Data Analysis and Knowledge Discovery, 2019, 3(7): 1-13.
[17] RITTER A, ETZIONI O.A Latent Dirichlet Allocation Method for Selectional Preferences[C]// Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics. Uppsala: Association for Computational Linguistics, 2010: 424-434.
[18] 郭羽婷, 姚宣合. 基于主题挖掘和情感分析的在线健康社区用户评论研究[J]. 现代情报, 2025, 45(8): 135-145.
GUO Y T, YAO X H.Research on User Reviews of Online Health Community Based on Topic Mining and Sentiment Analysis[J]. Journal of Modern Information, 2025, 45(8): 135-145.
[19] 胡泽文, 王梦雅, 韩雅蓉. 基于LDA2Vec-BERT的新兴技术主题多维指标识别与演化分析研究——以颠覆性技术领域: 区块链为例[J]. 现代情报, 2024, 44(9): 42-58.
HU Z W, WANG M Y, HAN Y R.Multidimensional Indicator Identification and Evolution Analysis of Emerging Technology Topics Based on LDA2Vec-BERT—A Case Study of Blockchain Technology in the Field of Disruptive Technology[J]. Journal of Modern Information, 2024, 44(9): 42-58.
[20] 徐建国, 王旭阳. 一种基于词加权LDA模型的恶意文件检测方法[J]. 计算机应用与软件, 2024, 41(3): 313-320.
XU J G, WANG X Y.A Malicious File Detection Method Based on “Key Words” Weighted Lda Model[J]. Computer Applications and Software, 2024, 41(3): 313-320.
[21] 范柏乃, 盛中华. 数字经济安全的维度识别、特征提取及分层模型——基于LDA主题分析与扎根理论编码的混合研究[J]. 浙江大学学报(人文社会科学版), 2024, 54(2): 5-29.
FAN B N, SHENG Z H. Dimension Identification, Feature Extraction and Layered Model of Digital Economy Security: A Mixed Research of LDA Thematic Analysis and Grounded Theory Coding[J]. Journal of Zhejiang University (Humanities and Social Sciences), 2024, 54(2): 5-29.
[22] 李秀霞, 程结晶, 韩霞. 发文趋势与引文趋势融合的学科研究主题优先级排序——以我国情报学学科主题为例[J]. 图书情报工作, 2019, 63(11): 88-95.
LI X X, CHENG J J, HAN X.The Prioritization of Subject Research Topics Based on the Integration of Writing Trends and Citation Trends: Taking the Subject of Information Science in China as an Example[J]. Library and Information Service, 2019, 63(11): 88-95.
[23] BLEI D M, NG A Y, JORDAN M I.Latent Dirichlet Allocation[J]. Journal of Machine Learning Research, 2003, 3(1): 993-1022.
[24] 石小涛, 郭霞, 鲁子涵, 等. 基于感性工学的驾舱座椅CMF研究及中式元素设计应用[J]. 包装工程, 2023, 44(6): 441-448.
SHI X T, GUO X, LU Z H, et al.CMF Design and Application of Chinese Elements in Cockpit Seat Based on Kansei Engineering[J]. Packaging Engineering, 2023, 44(6): 441-448.
[25] 李艳春. 论社会交换的概念与形式[J]. 求索, 2014(1): 126-130.
LI Y C.On the Concept and Form of Social Exchange[J]. Seeker, 2014(1): 126-130.
[26] 杭敏, 黄培智. 文创何以“出圈”: 论传统文化的物质性转化与价值性延展[J]. 新闻与写作, 2024(2): 25-34.
HANG M, HUANG P Z.Why the Cultural Creation "out of the Circle": On the Material Transformation and Value Extension of Traditional Culture[J]. News and Writing, 2024(2): 25-34.
[27] 张静, 束霞平. 基于文化转译理念下甪直水乡妇女服饰的数字文创设计路径[J]. 工业工程设计, 2024, 6(4): 55-62.
ZHANG J, SHU X P.Digital Cultural and Creative Design Path ofWomen's Clothing in LuzhiWaterTownship Based on the Concept of Cultural Translation[J]. Industrial&engineering Design, 2024, 6(4): 55-62.
[28] 毕学锋, 华焓亦, 王舟薇. 数字时代下新文创的文化挖掘与重塑[J]. 工业工程设计, 2023, 5(6): 19-24.
BI X F, HUA H Y, WANG Z W.Cultural Excavation and Remolding of New Cultural Creation in the Digital Age[J]. Industrial&Engineering Design, 2023, 5(6): 19-24.
[29] 张雪, 王凤彬. 生态系统向心力与离心力的演变——基于小米生态链的纵向案例研究[J]. 中国工业经济, 2023(9): 174-192.
ZHANG X, WANG F B.Evolution of Centripetal and Centrifugal Forces of Ecosystem: A Longitudinal Case Study of Xiaomi Ecosystem[J]. China Industrial Economics, 2023(9): 174-192.
[30] 肖人彬, 林文广. 数据驱动的产品创新设计研究[J]. 机械设计, 2019, 36(12): 1-9.
XIAO R B, LIN W G.Research on Data-Driven Product Innovation Design[J]. Journal of Machine Design, 2019, 36(12): 1-9.
[31] SHANNON C E.A Mathematical Theory of Communication[J]. The Bell System Technical Journal, 1948, 27(3): 379-423.
[32] LI L H, MO R.Production Task Queue Optimization Based on Multi-Attribute Evaluation for Complex Product Assembly Workshop[J]. PLoS One, 2015, 10(9): e0134343.