摘要：

Abstract:

【Purpose/significance】The government WeChat public account is an important channel for the government to communicate

with the public. The evaluation of the information quality of the government WeChat public account helps the government to establish

a prestige image and enhances the government's credibility.【Method/process】Based on the“5W propagation”model, 39 evaluation

indicators were initially obtained from the five dimensions of information productivity, information content, information performance,

users and information influence. The Rough Set theory (RS) reduction was used as 11 core indicators and comprehensive evaluation

was carried out. The evaluation results are used as input data to simulate and train the BP neural networks. After training successfully,

the RS-BP neural networks information quality evaluation model of the government WeChat public accounts is generated, which is ap⁃

plied to the empirical analysis of 4 different types of typical government WeChat public accounts in Jiangxi.【Result/conclusion】The

empirical research shows that this model has certain applicability in dealing with the non-linear problem of government WeChat pub⁃

lic accounts information quality evaluation, which can provide reference for the evaluation and improvement of government information

quality.【Innovation/limitation】The RS-BP neural networks information quality evaluation model of the government WeChat public ac⁃

counts has practical value, but the types of survey objects are not extensive enough, and training data is insufficient. The maturity of

the model needs further improvement.