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Microblog Emotion Analysis Using Improved DBN Under Spark Platform

Microblog Emotion Analysis Using Improved DBN Under Spark Platform

Wanjun Chang, Yangbo Li, Qidong Du
Copyright: © 2023 |Volume: 16 |Issue: 2 |Pages: 16
ISSN: 1935-570X|EISSN: 1935-5718|EISBN13: 9781668488676|DOI: 10.4018/IJITSA.318141
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MLA

Chang, Wanjun, et al. "Microblog Emotion Analysis Using Improved DBN Under Spark Platform." IJITSA vol.16, no.2 2023: pp.1-16. http://doi.org/10.4018/IJITSA.318141

APA

Chang, W., Li, Y., & Du, Q. (2023). Microblog Emotion Analysis Using Improved DBN Under Spark Platform. International Journal of Information Technologies and Systems Approach (IJITSA), 16(2), 1-16. http://doi.org/10.4018/IJITSA.318141

Chicago

Chang, Wanjun, Yangbo Li, and Qidong Du. "Microblog Emotion Analysis Using Improved DBN Under Spark Platform," International Journal of Information Technologies and Systems Approach (IJITSA) 16, no.2: 1-16. http://doi.org/10.4018/IJITSA.318141

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Abstract

In order to solve the problems that traditional single-machine methods find it difficult to complete the task of emotion classification quickly, and the time efficiency and scalability are not high; a microblog emotion analysis method using improved deep belief network (DBN) under Spark platform is proposed. First, the Hadoop distributed file system is used to realize the distributed storage of text data, and the preprocessed data and emotion dictionary are converted into word vector representation based on the continuous bag-of-words model. Then, an improved DBN model is constructed by combining the adaptive learning method of DBN with the active learning method, and it is applied to the learning analysis of text word vectors. Finally, the data parallel optimization of the improved DBN model is realized, based on Spark platform to accurately and quickly obtain the emotion types of microblog texts. The experimental analysis of the proposed method based on the microblog text data set shows that the classification accuracy is more than 94%.