Title: Campus public opinion analysis based on LSTM neural network

Authors: Yuanfen Tu; Bin Yang

Addresses: School of Business Administration, Nanchang Institute of Technology, Nanchang, 330099, China ' School of Business, Jiangxi Institute of Applied Science and Technology, Nanchang, 330100, China

Abstract: In the past decades, public opinion in campus has shown a high incidence trend. Various new media accelerates the diffusion of public opinion. It poses a major challenge to the management of universities. In this paper, a campus public opinion (CPO) analysis model on the basis of long short-term memory (LSTM) is proposed. The new approach, called CPOLSTM, is composed of five operations: data collection, data preprocessing, training and testing, prediction, and decision making. To verify the performance of CPOLSTM, it is compared with two other approaches. Simulation results demonstrate the proposed CPOLSTM can effectively identify the development trend of CPO.

Keywords: CPO; campus public opinion; LSTM; long short-term memory; neural network; machine learning; prediction model.

DOI: 10.1504/IJCSM.2025.147471

International Journal of Computing Science and Mathematics, 2025 Vol.21 No.3, pp.245 - 252

Received: 24 Feb 2025
Accepted: 13 May 2025
Published online: 16 Jul 2025 *

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