金融领域的深度学习评估推特情绪的影响和对股票的预测
1Maynooth International Engineering College, Fuzhou University, Fuzhou, Fujian, China.
PeerJ. Computer science
|June 10, 2024
概括
社交媒体情绪分析可以预测股票市场的变化. 机器学习模型揭示了公众在Twitter上的情绪与股票价格波动之间的重要联系,有助于财务预测.
科学领域:
- 计算社会科学 计算社会科学
- 金融市场分析 金融市场分析
- 机器学习应用程序 机器学习应用程序
背景情况:
- 社交媒体产生了大量的公众情绪数据.
- 这些数据为市场趋势分析提供了机会.
- 现有的情绪分析模型需要根据金融环境进行调整.
研究的目的:
- 量化社交媒体情绪与股票市场波动之间的相关性.
- 改进金融市场相关推文的情绪分析模型.
- 探索公众情绪对股票价格的预测力.
主要方法:
- 调整了一个先前存在的情绪分析算法.
- 开发并验证了一个使用Twitter数据对金融市场的模型.
- 采用了定量分析和方法测试.
主要成果:
- 确定了推特情绪和股票市场活动之间的统计学意义上的关系.
- 演示了精致模型检测微妙情绪线索的能力.
- 建立了公众情绪和随后的股价变化之间的联系.
结论:
- 基于机器学习的情绪分析为金融专家提供了宝贵的见解.
- 整合这些模型可以增强经济预测能力.
- 社交媒体情绪是市场行为的可量化的预测指标.
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