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- W4367153013 abstract "Market sentiment is the attitude or feeling that traders or investors have about a company, industry, or financial market. Day traders and technical analysts rely on market sentiment, as it influences the price movement of a stock. Sentiment analysis is a natural language processing approach to analyze market sentiment. In this work, we analyze the effect of the news on stock price trends on the Kuala Lumpur Stock Exchange or Bursa Malaysia. Specifically, we analyze the financial news headlines involving one or more listed companies and determine whether it will move the stock price up, down, or flat. We propose a deep neural network architecture with name attention to model the relationship between a news headline and the stock price trend. The main idea of the approach is to focus on the target company in the headline when modeling the relationship between a headline and the stock trend using attention. The experiment result shows that the proposed approach performs better than other baseline approaches in terms of accuracy, precision, recall, and f1." @default.
- W4367153013 created "2023-04-28" @default.
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- W4367153013 date "2023-01-01" @default.
- W4367153013 modified "2023-09-25" @default.
- W4367153013 title "A Deep Learning Model with Name Attention to Predict the Stock Trend from News Headline" @default.
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- W4367153013 doi "https://doi.org/10.1007/978-981-19-8406-8_29" @default.
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