Title: Research and judgement method of social network hot news public opinion based on knowledge graph

Authors: Gelang Li

Addresses: Fuyang Normal University, Fuyang 236000, China

Abstract: In order to improve the accuracy of the judgement of the development of news public opinion, this paper puts forward the research and judgement method of social network hot news public opinion based on knowledge graph. Through corpus annotation, character coding and time slice processing, the corpus of hot news on the internet is pre-processed, and the processed corpus information is used to construct knowledge atlas. In order to improve the accuracy of the analysis of news elements, the map is composed of several sub-maps with the most closely connected relationship. Finally, in combination with the real-time nature of news, the development of news public opinion is judged from the three perspectives of news evolution, spread and news heat. The test results show that the error of the method is less than 2% for the judgement of public opinion evolution degree, spread breadth and news heat.

Keywords: knowledge graph; hot news on social networks; public opinion research and judgement; corpus processing; connectivity relation; real time.

DOI: 10.1504/IJWBC.2024.136673

International Journal of Web Based Communities, 2024 Vol.20 No.1/2, pp.63 - 74

Received: 16 Feb 2022
Accepted: 09 Jun 2022
Published online: 15 Feb 2024 *

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