Research and analysis of psychological data based on machine learning methods Online publication date: Wed, 27-Apr-2022
by Guangshun Chen; Wei Lv; Junwei Ma; Yanchun Liang
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 22, No. 1, 2022
Abstract: The integration of psychology and computer science has become the mainstream contemporary research method on psychological data. Weibo, China's largest open platform for communication and information sharing between users, has many emotional contents hidden in its data. According to the current trend, the Weibo data are segmented by machine learning to obtain a psychological portrait of Weibo users. This design uses Long and Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNNs) to perform sentiment classification on Weibo data. The classification results are analysed using word frequency analysis and the Latent Dirichlet Allocation (LDA) model to obtain portraits of Weibo users' sentiment and an analysis of the results. The results are displayed in the form of word clouds. According to the clustering results of the word clouds, the main factors affecting different polar emotions can be analysed.
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