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This project is aiming to solve financial problems with the implementation of specific 2 models： LDA(Latent Dirichlet Allocation) and word2vec, where LDA is a generative probabilistic model for collections of discrete data and word2vec is a tool for word-embedding based on deep learning. We try to determine the degree to which the research reports can be true to financial market dynamics and whether they are forward-looking or just second-guessers. Papers here: English Version
(not completed) 
We would like to say thanks to MingWen Liu from ShiningMidas Private Fund for his generous help throughout the research. We are also grateful to Xingyu Fu from Sun Yat-sen University for his guidance and help. With their help, this research has been completed successfully.
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