BERT-Based Stock Market Sentiment Analysis

Chien Cheng Lee, Zhongjian Gao, Chun Li Tsai

研究成果: Conference contribution

摘要

This paper explores the performance of natural language processing in financial sentiment classification. We collected people's views on U.S. stocks from the Stocktwits website. The messages on this website reflect investors' views on the stock. These messages are classified into positive or negative sentiments using a BERT-based language model. Investor sentiment can be further analyzed to help more investors, businesses or organizations make effective decisions. The experimental results show that the pre-trained BERT model has been fine-tuned on the labeled sentiment dataset, and can recognize the sentiment of investors with an accuracy of more than 87.3%.

原文English
主出版物標題2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781728173993
DOIs
出版狀態Published - 2020 九月 28
事件7th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020 - Taoyuan, Taiwan
持續時間: 2020 九月 282020 九月 30

出版系列

名字2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020

Conference

Conference7th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020
國家/地區Taiwan
城市Taoyuan
期間20-09-2820-09-30

All Science Journal Classification (ASJC) codes

  • 電腦網路與通信
  • 人工智慧
  • 電腦科學應用
  • 訊號處理
  • 電氣與電子工程
  • 儀器

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