Intelligent classification algorithm for air pollution-related microblog texts with public perception

Zhong Li; Min Ji; Yong Sun; Yunxiu Han

doi:10.1117/12.2625583

9 December 2021 Intelligent classification algorithm for air pollution-related microblog texts with public perception

Zhong Li, Min Ji, Yong Sun, Yunxiu Han

Proceedings Volume 12129, International Conference on Environmental Remote Sensing and Big Data (ERSBD 2021); 121290L (2021) https://doi.org/10.1117/12.2625583
Event: 2021 International Conference on Environmental Remote Sensing and Big Data, 2021, Wuhan, China

Abstract

In order to achieve intelligent classification of air pollution-related microblog texts with semantically mixed public perception, with the help of the Word2Vec model developed by Google, this paper uses a large number of microblog texts as the training set for word vectors training, the trained word vectors are embedded in convolutional neural network (referred to as CNN) model. Based on the established classification criteria of gaseous pollution, dust pollution, smoke pollution and haze pollution, the 1000 air pollution-related microblogs were screened out to design and implement an automatic and intelligent classification algorithm. The experimental results show that the overall accuracy rate is 94.75% and the overall recall rate is 94.50%, which can meet the accurate classification of air pollution-related microblog texts, and provide accurate corpus data for later analysis of the semantic features of air pollution topics and the public's perceived emotional intensity.

Citation Download Citation

Zhong Li, Min Ji, Yong Sun, and Yunxiu Han "Intelligent classification algorithm for air pollution-related microblog texts with public perception", Proc. SPIE 12129, International Conference on Environmental Remote Sensing and Big Data (ERSBD 2021), 121290L (9 December 2021); https://doi.org/10.1117/12.2625583

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KEYWORDS

Pollution

Air contamination

Classification systems

Convolution

Data modeling

Statistical modeling

Algorithm development

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