Update README.md

README.md

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 ---
-license: mit
+annotations_creators:
+- other
+language:
+- en
+language_creators:
+- other
+license:
+- mit
+multilinguality:
+- monolingual
+pretty_name: twitter financial news
+size_categories:
+- 10K<n<100K
+source_datasets:
+- original
+tags:
+- twitter
+- finance
+- markets
+- stocks
+- wallstreet
+- quant
+- hedgefunds
+- markets
+task_categories:
+- text-classification
+task_ids:
+- multi-class-classification
 ---
+
+### Dataset Description
+
+The Twitter Financial News dataset is an English-language dataset containing an annotated corpus of finance-related tweets. The dataset is split into two groups:
+
+1. Topic classification: 21,107 documents annotated with 20 labels:
+
+```python
+topics = {
+    "LABEL_0": "Analyst Update",
+    "LABEL_1": "Fed | Central Banks",
+    "LABEL_2": "Company | Product News",
+    "LABEL_3": "Treasuries | Corporate Debt",
+    "LABEL_4": "Dividend",
+    "LABEL_5": "Earnings",
+    "LABEL_6": "Energy | Oil",
+    "LABEL_7": "Financials",
+    "LABEL_8": "Currencies",
+    "LABEL_9": "General News | Opinion",
+    "LABEL_10": "Gold | Metals | Materials",
+    "LABEL_11": "IPO",
+    "LABEL_12": "Legal | Regulation",
+    "LABEL_13": "M&A | Investments",
+    "LABEL_14": "Macro",
+    "LABEL_15": "Markets",
+    "LABEL_16": "Politics",
+    "LABEL_17": "Personnel Change",
+    "LABEL_18": "Stock Commentary",
+    "LABEL_19": "Stock Movement",
+}
+```
+
+2. Sentiment analysis: 11,932 documents annotated with 3 labels:
+
+```python
+sentiments = {
+    "LABEL_0": "Bearish", 
+    "LABEL_1": "Bullish", 
+    "LABEL_2": "Neutral"
+}  
+```
+
+The data was collected using the Twitter API. The current dataset supports the multi-class classification task.
+
+### Task 1: Sentiment Analysis
+
+# Data Splits
+There are 2 splits: train and validation. Below are the statistics:
+
+| Dataset Split | Number of Instances in Split                |
+| ------------- | ------------------------------------------- |
+| Train         | 9,938                                       |
+| Validation    | 2,486                                       |
+
+
+### Task 2: Topic Classification
+
+# Data Splits
+There are 2 splits: train and validation. Below are the statistics:
+
+| Dataset Split | Number of Instances in Split                |
+| ------------- | ------------------------------------------- |
+| Train         | 16,990                                      |
+| Validation    | 4,118                                       |
+
+
+# Licensing Information
+The Twitter Financial Dataset