情报科学 ›› 2025, Vol. 43 ›› Issue (3): 17-24.

• 理论研究 • 上一篇    下一篇

基于文本挖掘的老年群体数字融入影响因素研究

  

  • 出版日期:2025-03-05 发布日期:2025-05-27

  • Online:2025-03-05 Published:2025-05-27

摘要: 【目的/意义】识别并分析老年群体数字融入的关键影响因素及层级关系,为政府制定有效的政策措施提 供理论参考。【方法/过程】以评论文本作为研究对象,利用LDA主题模型挖掘识别老年数字融入的重要影响因素, 然后利用DEMATEL-ISM模型对各个影响因素的重要程度及层次关系进行分析研究。【结果/结论】研究结果表明, 老年群体数字融入受到个体、技术、社会和政府4个层面,共9个因素的影响,其中数字技术交互、数字文化氛围、数 字技术安全保障、政策措施、数字素养水平是影响老年群体数字融入的关键因素。基础设施建设和政策措施是底 层因素,具有保障性和导向性作用;心理动机情况处于表层因素,受到所有层次因素的影响。【创新/局限】运用文本 挖掘的方法,从评论文本中提取老年群体数字融入的影响因素,构建了层级关系模型,为老年群体数字融入提供了 新的视角和分析工具。未来数据源和模型的适用性和稳健性有待进一步验证。

Abstract: 【Purpose/significance】Identify and analyze the key influencing factors and hierarchical relationships of the digital inclu⁃ sion of the elderly, and provide theoretical reference for the government to formulate effective policy measures.【Method/process】Tak⁃ ing the review text as the research object, the LDA topic model was used to mine and identify the important influencing factors of the digital integration of the elderly, and then the DEMATEL-ISM model was used to analyze and study the importance and hierarchical relationship of each influencing factor.【Result/conclusion】The research results show that the digital integration of the elderly is af⁃ fected by a total of 9 factors at 4 levels: individual, technology, society and government, including digital technology interaction, digital cultural atmosphere, digital technology security, policy measures, digital literacy level is a key factor affecting the digital integration of the elderly. Infrastructure construction and policy measures are the underlying factors, which play a protective and guiding role; psy⁃ chological motivational conditions are surface factors and are affected by factors at all levels【. Innovation/limitation】Use text mining methods to extract the influencing factors of the digital inclusion of the elderly from the review text, and construct a hierarchical rela⁃ tionship model, which provides a new perspective and analysis tool for the digital inclusion of the elderly. The applicability and robust⁃ ness of future data sources and models need to be further verified.