docs: update dataset information

README.md

@@ -1,3 +1,33 @@
----
-license: ecl-2.0
----
+---
+license: ecl-2.0
+task_categories:
+- text-classification
+language:
+- en
+tags:
+- public
+- text
+- education
+- sentiment-analysis
+pretty_name: Tweet Feels 1M6
+size_categories:
+- 1M<n<10M
+---
+
+Sentiment140
+
+Collection of over a million English-language tweets harvested through the Twitter API in 2009. Each tweet carries a sentiment label automatically inferred from the presence of positive or negative emoticons: 0 for negative and 4 for positive (the original release also encodes 2 for neutral, though this class is sparsely populated).  
+
+The dataset is distributed as a single CSV file with six tab-separated fields:  
+
+- **target** – sentiment polarity (0, 2, 4)  
+- **ids** – unique tweet ID  
+- **date** – UTC timestamp of posting  
+- **flag** – search query that matched the tweet, or “NO_QUERY”  
+- **user** – screen name of the posting account  
+- **text** – full tweet text, emoticons and URLs preserved  
+
+No manual annotation was performed; labels were assigned via distant supervision based on emoticon presence. The corpus covers diverse topics and informal language patterns typical of Twitter, making it a standard benchmark for large-scale sentiment analysis and social-media text-mining tasks.
+
+**Acknowledgements**
+The dataset is available through [Kaggle—Sentiment140](https://www.kaggle.com/datasets/kazanova/sentiment140?resource=download).