Update README.md

README.md

@@ -37,26 +37,26 @@ The Twitter Financial News dataset is an English-language dataset containing an
 
 ```python
 topics = {
-    0:'Analyst Update',
-    1:'Fed | Central Banks',
-    2:'Company | Product News',
-    3:'Treasuries | Corporate Debt',
-    4:'Dividend',
-    5:'Earnings',
-    6:'Energy | Oil',
-    7:'Financials',
-    8:'Currencies',
-    9:'General News | Opinion',
-    10:'Gold | Metals | Materials',
-    11:'IPO',
-    12:'Legal | Regulation',
-    13:'M&A | Investments',
-    14:'Macro',
-    15:'Markets',
-    16:'Politics',
-    17:'Personnel Change',
-    18:'Stock Commentary',
-    19:'Stock Movement'
+    "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",
 }
 ```
 
@@ -64,10 +64,10 @@ topics = {
 
 ```python
 sentiments = {
-    0:'bearish', 
-    1:'bullish',
-    2:'neutral'
-}    
+    "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.