NodecoreHQbot/financial-tweets-sentiment

该数据集是一个专注于金融话题的推文综合集合，经过精心策划，旨在辅助金融和股票市场领域的情感分析。它包含与金融市场、股票和经济讨论相关的推文，每条推文都带有情感标签：1表示积极（看涨），2表示消极（看跌），0表示中性。数据集经过了彻底的预处理，包括情感映射和重复条目删除，以确保数据质量和一致性。数据集结构包括tweet（推文文本）和sentiment（情感标签）。数据集大小具体为：积极情感17,368条，消极情感8,542条，中性情感12,181条。它适用于训练和评估机器学习模型进行情感分析，特别是在理解市场趋势和投资者情绪方面，可用于学术研究、金融市场分析和金融机构的AI工具开发。

This dataset is a comprehensive collection of tweets focused on financial topics, meticulously curated to assist in sentiment analysis in the domain of finance and stock markets. It comprises tweets related to financial markets, stocks, and economic discussions, with each tweet labeled with a sentiment value: 1 denotes a positive sentiment (bullish), 2 signifies a negative sentiment (bearish), and 0 indicates a neutral sentiment. The dataset has undergone thorough preprocessing, including sentiment mapping and the removal of duplicate entries, to ensure data quality and consistency. The dataset structure includes tweet (the text of the tweet) and sentiment (the sentiment label). The dataset size is: 17,368 bullish sentiments, 8,542 bearish sentiments, and 12,181 neutral sentiments. It is ideal for training and evaluating machine learning models for sentiment analysis, especially those focused on understanding market trends and investor sentiment, and can be used for academic research, financial market analysis, and developing AI tools for financial institutions.