Title: Intelligent evaluation method for multimedia network public opinion decline period based on multi-divisional optimisation

Authors: Xuefang Zhou

Addresses: College of Chinese Language and Culture, Zhejiang Yuexiu University, Shaoxing, 312000, China

Abstract: In order to overcome the long data collection time, low accuracy in extracting features of public opinion decline, and low precision rate associated with traditional methods, a new intelligent evaluation method for multimedia network public opinion decline period based on multi-divisional optimisation is proposed. An evaluation index system for intelligent evaluation of public opinion decline period is constructed, and index data is collected and processed. The multiple fractal dimensions of the index data are determined, and multi-divisional optimisation is performed in conjunction with nonlinear support vector machines to extract features of public opinion decline. Public opinion decline period intelligent evaluation is achieved based on these features and the BiLSTM model. The experimental results show that the average data collection time of the proposed method is 0.72 s, the average accuracy of feature extraction of public opinion decline is 97.66%, and the precision rate is consistently above 95%.

Keywords: multi-divisional optimisation; multimedia network; public opinion decline period; intelligent evaluation; nonlinear support vector machine; BiLSTM model.

DOI: 10.1504/IJBIDM.2025.145361

International Journal of Business Intelligence and Data Mining, 2025 Vol.26 No.3/4, pp.329 - 345

Received: 08 Dec 2023
Accepted: 02 Aug 2024
Published online: 31 Mar 2025 *

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