现代情报2024，Vol.44Issue(9)：42-58,17.DOI:10.3969/j.issn.1008-0821.2024.09.004
基于LDA2Vec-BERT的新兴技术主题多维指标识别与演化分析研究
Multidimensional Indicator Identification and Evolution Analysis of Emerging Technology Topics Based on LDA2Vec-BERT
摘要
Abstract
[Purpose/Significance]Mining and visualizing the global disruptive technology,such as the emerging and hot technical topics and their evolution differences implied in the global blockchain patent literature can provide for practi-tioners in the field,science and technology policy makers,management departments and science and technology research and development personnel.[Method/Process]Based on the patent literature in the global blockchain field,different time slices were divided in a timely order.LDA topic model,Word2vec word vector model,and BERT language model were comprehensively utilized to build the technical topic mining model in the blockchain field.At the same time,four-dimension-al indicators,including topic popularity,topic population,topic technicality and topic novelty were constructed to identify the hot technology topics and emerging technology topics in the field of blockchain.These were then combined with the topic evolution model to carry out evolutionary analysis on the emerging hot topics.[Result/Conclusion]The research finds that the LDA2Vec-BERT topic recognition and evolution model could identify emerging and hot technical topics in the field based on the massive patent literature in the field of blockchain,and visually and clearly displays the evolution trend and characteristics of the topic of blockchain technology,and finds the development trend of blockchain technology from archi-tecture research to application research.By comparing the model results,it can be found that the empirical results are rea-sonable,and the accuracy rate,recall rate and F1 value of the model are higher than other recognition models,which proves that the method has the good effect on the recognition of disruptive technology topics.关键词
区块链专利/LDA主题模型/Word2vec模型/BERT模型/新兴技术主题/热点技术主题/主题识别/主题演化Key words
blockchain patents/LDA topic model/Word2vec model/BERT model/emerging topics/hot topics/topic mining/topic evolution分类
社会科学引用本文复制引用
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[J].现代情报,2024,44(9):42-58,17.基金项目
国家社会科学基金重大项目"前沿交叉领域识别与融合创新路径与预测方法研究"(项目编号:23&ZD225). （项目编号:23&ZD225）
