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Stock Investors' Preferences on Stock Forum Topics Based on FNS-LDA2vec
  • GANG-LONG DUAN,
  • JIN-KAI ZHANG,
  • MING-YUE JIANG
GANG-LONG DUAN
Xi'an University of Technology School of Economics and Management
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JIN-KAI ZHANG
Xi'an University of Technology School of Economics and Management

Corresponding Author:[email protected]

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MING-YUE JIANG
Xi'an University of Technology School of Economics and Management
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Abstract

This article constructs an investor topic preference mining model through stock bar text data and the FNS-LDA2vec method. Firstly, dynamic topic mining of the LDA model is achieved by dividing user documents in the stock community by time. Then, by combining the improved LDA topic model and the Word2vec word vector model, a dynamic mining model of stock bar user topic preference based on FNS-LDA2vec is constructed, and topic representation is learned through the joint learning of document vectors and word vectors. Finally, empirical results show that the topic extraction model constructed in this article is superior to the comparison model. The model has broad application value in personalized recommendation for investors and stock prediction.