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2023 , Vol. 67 >Issue 7: 92 - 106

DOI: https://doi.org/10.13266/j.issn.0252-3116.2023.07.009

INFORMATION RESEARCH

High-Value Hot Topic Identification and Evolutionary Path Analysis Based on Dynamic Semantic Network

  • Teng Jie ,
  • Liu Li ,
  • Li Shuo ,
  • Hu Guangwei
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  • 1 School of Information Management, Nanjing University, Jiangsu 210023;
    2 Government Data Resources Institution, Nanjing University, Jiangsu 210023

Received date: 2022-08-31

  Revised date: 2022-10-28

  Online published: 2023-04-15

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Abstract

[Purpose/Significance] Effectively and accurately identify the theme of social demands, grasp the transformation nodes of social demands, and track the evolution trend of the theme, so as to provide support for the harmonious and orderly development of government services and social governance.[Method/Process] A set of high-value topic identification and evolution path analysis methods based on semantic web was proposed. Firstly, based on the idea of local contextual semantic parsing, this study used lexical co-occurrence networks to construct a dynamic semantic relational network; Secondly, this study used community discovery algorithm to identify sub communities, used RFM model was applied to divide the value of keywords and topic tags was identified according to high value keywords, and then the topic evolution relationship was reflected by measuring the topic similarity in adjacent time intervals; Finally, the model was verified with the social appeal data of Shanghai, and the theme recognition effect was compared with the K-means method. The accuracy rate, recall rate and F1 value were used to evaluate the effect of the method.[Result/Conclusion] All the three indicators are above the 0.3 cut-off values, proving significant optimization effects have been achieved. This study can build a panoramic view of public concerns reflected in the mailbox module of government website leaders, and also provide new ideas for exploring other social text mining methods and supporting the big data analysis practice of national governance.

Key words： semantic relationships; social appeals; topic identification; topic evolutionary path; Word2Vec

Cite this article

Teng Jie , Liu Li , Li Shuo , Hu Guangwei . High-Value Hot Topic Identification and Evolutionary Path Analysis Based on Dynamic Semantic Network[J]. Library and Information Service, 2023 , 67(7) : 92 -106 . DOI: 10.13266/j.issn.0252-3116.2023.07.009

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