h-Stock-News-Sentiment-Analysis-and-Visualization
所属分类：项目开发与运营
开发工具：Jupyter Notebook
文件大小：0KB
下载次数：0
上传日期：2024-03-18 10:40:22
上 传 者：
sh-1993
说明： 探索股票新闻情绪分析和可视化的财务决策。利用NLP技术和BERT模型微调，精度为85.46%。交互式Tableau仪表板，用于全面的情绪分布。为投资者提供数据驱动的见解。
(Explore Stock News Sentiment Analysis and Visualization for financial decision-making. Utilizes NLP techniques with BERT model fine-tuning for 85.46% accuracy. Interactive Tableau dashboard for comprehensive sentiment distribution. Empower investors with data-driven insights.)
文件列表:
Samar_StockSentiment _Dashboard .twbx
StockSentiment (4).csv
Stock_news_sentiment_analysis.ipynb
all-data.csv
# Enhancing-Investment-Decision-Making-Through-Stock-News-Sentiment-Analysis-and-Visualization
Explore Stock News Sentiment Analysis and Visualization for financial decision-making. Utilizes NLP techniques with BERT model fine-tuning for 85.46% accuracy. Interactive Tableau dashboard for comprehensive sentiment distribution. Empower investors with data-driven insights.
More on project
Enhancing investment strategies through Stock News Sentiment Analysis and Visualization, powered by advanced web scraping techniques using BeautifulSoup4. By scraping data from Finviz, gather real-time financial news headlines, laying the foundation for our comprehensive analysis.
Employing state-of-the-art Natural Language Processing (NLP) and fine-tuning the BERT model, we decipher sentiment nuances with an impressive 85.46% accuracy. Our initiative extends beyond analysis, as we construct interactive Tableau dashboards that provide a panoramic view of sentiment trends and patterns.
With an emphasis on accuracy and usability, we equip investors and traders with invaluable tools for navigating complex financial markets, revolutionizing decision-making processes. Join us in leveraging data-driven insights to unlock the full potential of investment opportunities.
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