Research on Social Media Feature Learning Algorithm Based on Deep Neural Network

Due to the rapid development of social media nowadays, a large amount of information, especially text-based information, is widely spread in social media, which exposes the defects of the original text mining technology. For a large amount of text data, a deep neural network can reduce the dimension...

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Bibliographic Details
Published in2022 IEEE 2nd International Conference on Power, Electronics and Computer Applications (ICPECA) pp. 590 - 594
Main Author Zhang, Ruijia
Format Conference Proceeding
LanguageEnglish
Published IEEE 21.01.2022
Subjects
big data
Deep learning
Deep neural network
feature learning
Fitting
Neural networks
Representation learning
social media
Social networking (online)
Text mining
Training
Online AccessGet full text
DOI10.1109/ICPECA53709.2022.9719080

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Summary:Due to the rapid development of social media nowadays, a large amount of information, especially text-based information, is widely spread in social media, which exposes the defects of the original text mining technology. For a large amount of text data, a deep neural network can reduce the dimensionality of a large number of text features, and increase the speed without compromising its accuracy. Based on this, this paper proposes a text feature extraction algorithm based on deep neural network, the main purpose is to improve the efficiency of current text mining, so as to improve the efficiency of modern social media use.
DOI:10.1109/ICPECA53709.2022.9719080