Update README.md

README.md

@@ -55,8 +55,8 @@ The dataset comprises tweets related to financial markets, stocks, and economic
 
 ## Dataset Size
 - **Bullish Sentiments**: 17,368
-- **Bearish Sentiments**: 14,383
-- **Neutral Sentiments**: 6,340
+- **Bearish Sentiments**: 8,542
+- **Neutral Sentiments**: 12,181
 
 ## Sources
 This dataset is an amalgamation of data from various reputable sources, each contributing a unique perspective on financial sentiment:
@@ -69,7 +69,7 @@ This dataset is an amalgamation of data from various reputable sources, each con
 - [Crypto Sentiment](https://github.com/surge-ai/crypto-sentiment/tree/main): Sentiment data for cryptocurrency-related tweets with 296 positive and 256 negative sentiments.
 - [Stock Sentiment](https://github.com/surge-ai/stock-sentiment/tree/main): Sentiment analysis on stock-related tweets, including 327 positive and 173 negative sentiments.
 - [Stockmarket Sentiment Dataset](https://www.kaggle.com/datasets/yash612/stockmarket-sentiment-dataset): Features 3685 positive and 2106 negative sentiments.
-- [Twitter Financial News Sentiment](https://huggingface.co/datasets/zeroshot/twitter-financial-news-sentiment): Contains 2398 positive, 7744 negative, and 1789 neutral sentiments.
+- [Twitter Financial News Sentiment](https://huggingface.co/datasets/zeroshot/twitter-financial-news-sentiment): Contains 2398 positive, 1789 negative, and 7744 neutral sentiments.
 
 ## Usage
 This dataset is ideal for training and evaluating machine learning models for sentiment analysis, especially those focused on understanding market trends and investor sentiment. It can be used for academic research, financial market analysis, and developing AI tools for financial institutions.