… According to different information richness, prediction time interval and classification … Neural
Network). The results show that the method has the best performance when the forecast time …

… During this period the use of Japanese was prohibited as part of the “de-Japanization” … and
use of Mandarin Chinese as the national standard language became mandatory, and the use …

… analysis, this paper explores the impacts of online news on stock market, aiming to improve
the accuracy of predicting … [Methods] First, we used the Convolutional Neural Network (CNN) …

… sentimental characteristics with the RoBERTa model and extracted the stock price characteristics
with the TCN network… the new RoBERTa-TCN model for stock price prediction. [Results] …

… stock market. [Methods] We used the LSTM deep neural networks to evaluate the sentiments
… [Limitations] The accuracy of sentiment analysis needs to be improved with more complex …

… According to different information richness, prediction time interval and classification …
Neural Network). The re-sults show that the method has the best performance when the forecast …

… the fluctuation of the stock index, providing new ideas for stock market risk prediction in China.
… indices and further optimizing the model to better analyze and predict stock market risks. …

… we shall argue that goodness of forecast is the metric by which model … neural network
problem was to express the outputs from a complex nonlinear model in simplified terms through a …

… The sentiment analysis techniques are then used in the task. Recently, the advent of social …
meta-data with a neural network in the revenue prediction task. Instead of predicting the exact …

… for online forums hotspot detection and forecast[J]. Decision Support Systems, 2010, 48(2): …
Twitter sentiment analysis with a deep neural network: An enhanced approach using user …