图书情报工作

图书情报工作 >

2025 , Vol. 69 >Issue 10: 62 - 73

DOI: https://doi.org/10.13266/j.issn.0252-3116.2025.10.006

研究论文

用户在线评论红山文化内容挖掘与情感分析

  • 高春玲 ,
  • 武小雨
展开
  • 1 辽宁师范大学管理学院 大连 116081;
    2 现代公共文化服务协调创新研究基地 大连 116081
高春玲，教授，博士，硕士生导师；武小雨，硕士研究生，通信作者，E-mail：1094314500@qq.com。

收稿日期: 2024-07-25

  修回日期: 2024-12-20

  网络出版日期: 2025-05-16

基金资助

本文系2022年国家社会科学基金一般项目“公共图书馆文旅融合高质量发展的内生动力及实现路径研究”(项目编号：22BTQ037)研究成果之一。

收起

User Online Reviews Hongshan Cultural Content Mining and Sentiment Analysis

  • Gao Chunling ,
  • Wu Xiaoyu
Expand
  • 1 School of Government, Liaoning Normal University, Dalian 116081;
    2 Modern Public Cultural Service Coordination Innovation Research Base, Dalian 116081
Gao Chunling, professor, PhD, master supervisor; Wu Xiaoyu, master candidate, corresponding author, E-mail: 1094314500@ qq.com.

Received date: 2024-07-25

  Revised date: 2024-12-20

  Online published: 2025-05-16

Supported by

This work is supported by the National Social Science Fund of China project titled “Research on the Endogenous Driving Force and Realization Path of the High-Quality Development of Cultural and Tourism Integration in Public Libraries” (Grant No. 22BTQ037).

Fold

摘要

[目的/意义] 在文化强国背景下，分析当前红山文化用户接收情况，挖掘红山文化传承存在的问题，从而为推动红山文化传承与推广提供有效建议。[方法/过程] 以红山文化有关的在线用户评论作为数据来源，利用词频分析对用户生成的文本评论进行初步分析；接着运用BERTopic模型进行主题识别；随后，通过情感分析方法解读用户在线评论的情感；最后，利用LDA主题聚类方法，进行积极词主题分类和消极词主题分类分析。[结果/结论] 目前，用户对红山文化历史遗址、服务体验、意义影响以及文化延伸较为关注。对于红山文化知识接收，用户表现出的积极情绪较多，这是促进红山文化传承、推动红山文化发展的重要依据。据此应积极深化智慧文旅平台建设、加强红山文化特色馆藏建设、重视社会力量参与并强化新媒体宣传推广模式，进而促进红山文化发展。

关键词： 在线评论; 红山文化; 内容挖掘; 情感分析

本文引用格式

高春玲 , 武小雨 . 用户在线评论红山文化内容挖掘与情感分析[J]. 图书情报工作, 2025 , 69(10) : 62 -73 . DOI: 10.13266/j.issn.0252-3116.2025.10.006

Abstract

[Purpose/Significance] Under the background of cultural power, this paper analyzes the current reception of Hongshan culture and explores the problems existing in the inheritance of Hongshan culture, so as to provide effective suggestions for promoting the inheritance and promotion of Hongshan culture. [Method/Process] Taking the online user comments related to Hongshan culture as the data source, the user-generated text comments were analyzed by word frequency analysis. The BERTopic model was used for topic recognition. Emotions of users’ online comments were interpreted through sentiment analysis methods. LDA topic clustering method was used to analyze the topic classification of the positive word and negative word. [Result/Conclusion] At present, users pay more attention to the historical sites, service experience, meaning influence, and cultural extension of the Hongshan culturale. For the reception of Hongshan cultural knowledge, users show more positive emotions, which is an important basis for promoting the inheritance and development of Hongshan culture. Accordingly, we should actively deepen the construction of intelligent cultural tourism platform, strengthen the construction of Hongshan cultural characteristic collection, attach importance to the participation of social forces, and strengthen the promotion mode of new media, so as to promote the development of Hongshan culture.

Key words： online reviews; Hongshan culture; content mining; sentiment analysis

参考文献

[1] 中国民族博物馆. 从红山文化探寻中华文明起源[EB/OL]. [2025-03-25]. https://www.cnmuseum.com/page_show.aspx?id=2351. (China Ethnic Museum. Exploring the origin of Chinese civilization from Hongshan culture [EB/OL]. [2025-03-25]. https://www.cnmuseum.com/page_show.aspx?id=2351.)
[2] 中国国家地理. 红山文化, 把中华文明史提前一千年[EB/OL]. [2025-03-25]. http://www.dili360.com/cng/article/p5350c3d6a38bb67.htm. (China National Geography. Hongshan culture advances the history of Chinese civilization by a thousand years [EB/OL]. [2025-03-25]. http://www.dili360.com/cng/article/p5350c3d6a38bb67.htm.)
[3] 程文婷, 吴家辉. 学前儿童数字阅读用户意见主题挖掘与情感分析研究[J]. 图书馆建设, 2022(3): 104-112. (CHENG W T, WU J H. Research on topic mining and sentiment analysis of digital reading opinions among preschool children [J]. Library development, 2022(3): 104-112.)
[4] 刘国祥. 红山文化研究[D]. 北京: 中国社会科学院研究生院, 2015. (LIU G X. Research on Hongshan Culture [D]. Beijing: Graduate School of Chinese Academy of Social Sciences, 2015.)
[5] 滨田耕作, 水野清一. 赤峰红山后[M]. 戴岳曦, 康英华, 译. 内蒙古: 内蒙古大学出版社, 2015. (HAMADA K, MIZUNO S. Hongshanhou in Chifeng [M]. DAI Y X, KANG Y H, trans. Inner Mongolia: Inner Mongolia University Press, 2015.)
[6] 刘莉. 中国新石器时代[M]. 陈星灿, 乔玉, 译. 北京: 文物出版社, 2007. (LIU L. In Chinese Neolithic Age[M]. CHEN X C, QIAO Y, trans. Beijing: Cultural Relics Publishing House, 2007)
[7] 朱乃诚. 苏秉琦晚年考古学研究探索的启示[J]. 文物春秋, 2020(2): 3-10, 31. (ZHU N C. Inspiration from the archaeological research explorations of SU B in his later years [J]. Cultural relics of spring and autumn periods, 2020(2): 3-10, 31.)
[8] 殷志强. 红山、良渚文化玉器的比较研究[J]. 北方文物, 1988(1): 8-12, 7. (YIN Z Q. Comparative study on Jade Artifacts of Hongshan and Liangzhu Cultures [J]. Northern cultural relics, 1988(1): 8-12, 7.)
[9] 徐昭峰, 尤彦婷. 试论红山文化的原始宗教系统[J]. 东北史地, 2014(6): 68-73. (XU Z F, YOU Y T. On the primitive religious system of Hongshan Culture [J]. Northeast historical geography, 2014(6): 68-73.)
[10] 梅靖波. 基于游客需求的赤峰红山文化旅游开发研究[D]. 北京: 北京林业大学, 2018. (MEI J B. Research on tourism development of Hongshan Culture in Chifeng based on tourist demand [D]. Beijing: Beijing Forestry University, 2018.)
[11] 林杨, 骆玉梅, 郭旭东. 文旅融合视角下的博物馆高质量发展研究——以红山文化博物馆为例[J]. 赤峰学院学报(汉文哲学社会科学版), 2024, 45(1): 83-86. (LIN Y, LUO Y M, GUO X D. Research on High-quality development of museums from the perspective of cultural and tourism integration: A case study of Hongshan Culture Museum [J]. Journal of Chifeng university (philosophy and social sciences edition), 2024, 45(1): 83-86.)
[12] 赵丽丽. 文旅融合视角下研学旅行基地建设研究——以赤峰市红山区为例[J]. 中学地理教学参考, 2023(18): 70-72. (ZHAO L L. Research on the construction of study travel bases from the perspective of cultural and tourism integration: a case study of Hongshan District, Chifeng City [J]. Reference for middle school geography teaching, 2023(18): 70-72.)
[13] 张紫琼, 叶强, 李一军. 互联网商品评论情感分析研究综述[J]. 管理科学学报, 2010, 13(6): 84-96. (ZHANG Z Q, YE Q, LI Y J. A review of sentiment analysis research on internet product reviews [J]. Journal of management science in China, 2010, 13(6): 84-96.)
[14] 李蕾, 彭慧, 刘晓娟. 大语言模型细粒度评论挖掘下的博物馆服务用户满意度研究[J]. 图书情报工作, 2024, 68(17): 54-67. (LI L, PENG H, LIU X J. Research on museum service user satisfaction based on Fine-Grained review mining using large language models [J]. Library and information work, 2024, 68(17): 54-67.)
[15] 汪圣, 任丽娟, 刘旭青, 等. 文旅融合视域下基于在线评论的“网红”城市书房形象感知研究[J]. 图书馆工作与研究, 2024(5): 45-53. (WANG S, REN L J, LIU X Q, et al. Research on the image perception of "Internet-famous" City Libraries based on online reviews from the perspective of cultural and tourism integration [J]. Library work and research, 2024(5): 45-53.)
[16] 孙传明, 陈熙, 王萍. 基于在线评论的非遗纪录片受众需求事理图谱构建研究[J]. 情报科学, 2023, 41(9): 107-114. (SUN C M, CHEN X, WANG P. Research on the construction of the Event-Action logic graph of audience demand for ICH documentaries based on online reviews [J]. Information science, 2023, 41(9): 107-114.)
[17] 钟静涵, 金武刚. 国内公共图书馆“场所”价值的公众认知研究——基于大众点评网在线评论文本分析[J]. 图书与情报, 2022(3): 20-30. (ZHONG J H, JIN W G. Research on public perception of the "Place" value of domestic public libraries: based on online review text analysis from Dianping.com [J]. Library & information, 2022(3): 20-30.)
[18] 黄佳佳, 李鹏伟, 彭敏, 等. 基于深度学习的主题模型研究[J]. 计算机学报, 2020, 43(5): 827-855. (HUANG J J, LI P W, PENG M, et al. Research on topic models based on deep learning [J]. Chinese journal of computers, 2020, 43(5): 827-855.)
[19] BLEI D M, YNG A, JORDAN M. Latent dirichlet allocation[J]. Journal of machine learning research, 2012, 3: 993-1022.
[20] 王洪伟, 高松, 陆頲. 基于LDA和SNA的在线新闻热点识别研究[J]. 情报学报, 2016, 35(10): 1022-1037. (WANG H W, GAO S, LU T. Research on online News hotspot recognition based on LDA and SNA [J]. Journal of the China Society for Scientific and Technical Information, 2016, 35(10): 1022-1037.)
[21] 王欣研, 张向先, 张莉曼. 学术APP用户在线评论主题语义关联研究[J]. 情报科学, 2020, 38(6): 25-31. (WANG X Y, ZHANG X X, ZHANG L M. Research on the semantic association of topics in online reviews of academic APP users [J]. Information science, 2020, 38(6): 25-31.)
[22] 叶川, 马静. 多媒体微博评论信息的主题发现算法研究[J]. 现代图书情报技术, 2015(11): 51-59. (YE C, MA J. Research on topic discovery algorithm for multimedia Weibo comment information [J]. Modern library and information technology, 2015(11): 51-59.)
[23] 王雪, 董庆兴, 张斌. 面向在线评论的用户需求分析框架与实证研究——基于KANO模型[J]. 情报理论与实践, 2022, 45(2): 160-167. (WANG X, DONG Q X, ZHANG B. Analytical framework and empirical study of user needs for online reviews based on KANO model[J]. Information studies: theory & application, 2022, 45(2): 160-167.)
[24] GROOTENDORST M. BERTopic: Leveraging BERT and c-TF-IDF to create easily interpretable Topics[EB/OL]. [2025-03-25]. https://doi.org/10.5281/zenodo.4430182.
[25] 沈棋琦, 张雪, 赵杨. 基于评论主题挖掘的移动图书馆App用户情感体验评价体系构建[J]. 图书馆学研究, 2023(4): 41-51. (SHEN Q Q, ZHANG X, ZHAO Y. Construction of an emotional experience evaluation system for mobile library App users based on review topic mining [J]. Research on library science, 2023(4): 41-51.)
[26] 谢法举, 刘臣, 唐莉.在线评论情感分析研究综述[J]. 软件导刊, 2018, 17(2): 1-4, 7. (XIE F J, LIU C, TANG L. Areview of sentiment analvsis in online reviews[J]. Journal of software guide, 2018, 17(2): 1-4, 7.)
[27] 李蕾, 彭慧, 刘晓娟.大语言模型细粒度评论挖掘下的博物馆服务用户满意度研究[J]. 图书情报工作, 2024, 68(17): 54-67. (LI L, PENG H, LIU X J. Research on museum service user satisfaction based on fine-grained review mining using large language models [J]. Library and information work, 2024, 68(17): 54-67.)
[28] MESSAOUDI C, GUESSOUM Z, BEN ROMDHANE L. Opinion mining in online social media: a survey[J]. Social network analysis and mining, 2022, 12(1): 25.
[29] 蒋翠清, 郭轶博, 刘尧. 基于中文社交媒体文本的领域情感词典构建方法研究[J]. 数据分析与知识发现, 2019, 3(2): 98-107. (JIANG C Q, GUO Y B, LIU Y. Research on the construction method of domain-specific sentiment lexicon based on Chinese social media text [J]. Data analysis and knowledge discovery, 2019, 3(2): 98-107.)
[30] 都平平, 郭琪, 李雨珂, 等. 基于社交媒体的网络学科信息交互推广服务[J]. 图书情报工作, 2014, 58(2): 84-90. (DU P P, GUO Q, LI Y K, et al. Interactive promotion service of discipline information based on social media networks[J]. Library and information service, 2014, 58(2): 84-90.)
[31] 王辉, 王晓玉, 李卫东, 等.在线健康社区重大慢病患者负面评论倾向的关键影响因素分析[J]. 情报科学, 2024, 42(6): 12-20, 28. (WANG H WANG X Y, LI W D, et al. Analysis of key factors influencing the negative review tendency of patients with major chronic diseases in online health communities [J]. Information science, 2024, 42(6): 12-20, 28.)
[32] 叶英平, 任志欣, 周昕. 基于在线消费评价的亲子阅读偏好可视化研究[J]. 情报科学, 2023, 41(5): 144-152, 160. (YE Y P, REN Z X, ZHOU X. A visual study on Parent-Child reading preferences based on online consumer reviews [J]. Information science, 2023, 41(5): 144-152, 160.)
[33] 李佳轩, 储节旺. 基于弹幕评论的在线知识社区用户关注度与情感度联合分析[J]. 数字图书馆论坛, 2023, 19(8): 68-76. (LI J X, CHU J W. Joint Analysis of users' attention and sentiment in online knowledge communities based on barrage comments [J]. Digital library forum, 2023, 19(8): 68-76.)
[34] 阎友兵, 郭亮宏. 基于网络文本的红色旅游游客情感特征研究——以韶山风景名胜区为例[J]. 湘潭大学学报(哲学社会科学版), 2020, 44(3): 131-136. (YAN Y B, GUO L H. Research on the emotional characteristics of red tourism visitors based on online text: a case study of Shaoshan Scenic Area [J]. Journal of Xiangtan University (philosophy and social sciences edition), 2020, 44(3): 131-136.)
[35] CAMPELLO R J G B, MOULAVI D, ZIMEK A, et al. Hierarchical density estimates for data clustering, visualization, and outlier detection[J]. ACM transactions on knowledge discovery from data, 2015, 10(1): 1-51.
[36] 陈洁. 基于Doc2Vec增强特征的长文本主题聚类研究[J]. 计算机科学, 2023, 50(S1): 221-226. (CHEN J. Research on long text topic clustering based on enhanced features using Doc2Vec [J]. Computer science, 2023, 50(S1): 221-226.
[37] “十四五”文物保护和科技创新规划[N]. 中国文物报, 2021-11-09(3). ("14th Five-Year Plan" for cultural relics protection and scientific and technological innovation [N]. China cultural relics newspaper, 2021-11-09(3).)
[38] 蓝紫琪, 刘欣. 高校图书馆特藏资源建设与服务调查分析——“双一流”高校图书馆与地方院校图书馆的差异比较[J]. 图书馆界, 2020(2): 59-66, 72. (LAN Z Q, LIU X. A survey and analysis of the construction and services of special collections in academic libraries: a comparative study between "double first-class" universities and local colleges [J]. Library world, 2020(2): 59-66, 72.)
[39] 常大伟, 刘菁菁. LAM(图书馆、档案馆、博物馆)协同服务的“碎片化”困境及其治理策略[J]. 山西档案, 2021(1): 21-26, 39. (CHANG D W, LIU J J. The "fragmentation" dilemma of collaborative services among LAM (libraries, archives, and museums) and its governance strategies [J]. Shanxi archives, 2021(1): 21-26, 39.)
[40] 周锦, 曹鲁娜. 社交网络赋能文化旅游深度融合：发展特征、作用机制与推进路径[J]. 南京社会科学, 2024(3): 151-162. (ZHOU J, CAO L N. Social networking empowers deep integration of cultural tourism: development characteristics, mechanism of action, and promotion path [J]. Nanjing social sciences, 2024(3): 151-162.)
Options
文章导航

/

〈 〉