An empirical study of the impact of biological information dissemination in social media on public science literacy

Autor: Tang Pei, Zhang Mengxiao
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
Druh dokumentu: article
ISSN: 2444-8656
DOI: 10.2478/amns.2023.2.01405
Popis: In this paper, we first establish a locally converged bioinformatics dataset based on gradient sampling and design an optimal data mining control model to improve the accuracy of bioinformatics big data feature mining. The performance of the Compressive Tracking algorithm and Online Bosting algorithm is compared with the mining error as a test index. At the same time, we propose a social media information dissemination algorithm applicable to large-scale social network datasets, taking the degree value of each node as the node’s full influence and comparing and analyzing the dissemination influence of BP-IM, RAND and MC-CELF algorithms. Finally, taking public health big data as the research object, the least squares regression method was used to analyze the influence of the amount of public attention to bioinformatics scientific knowledge on their scientific literacy in different media. The results showed that there was a significant positive correlation between scientific literacy and willingness to engage in science participation behavior on social media when the amount of public attention to scientific information was β =0225, p
Databáze: Directory of Open Access Journals