final

feature_extraction/liwc_from_text.py

@@ -4,7 +4,7 @@ import numpy as np
 import re
 from collections import defaultdict, Counter
 
-# Load the LIWC dictionary once
+# Load the LIWC dictionary
 def load_liwc_dic(dic_path="models/output.dic"):
     category_map = defaultdict(list)
     with open(dic_path, 'r', encoding='utf-8') as f:
@@ -17,7 +17,7 @@ def load_liwc_dic(dic_path="models/output.dic"):
             category_map[category] = words
     return category_map
 
-# Get LIWC vector from one input text
+# getting LIWC vector from input text
 def liwc_vector(text, category_map):
     tokens = re.findall(r"\b\w+\b", text.lower())
     counts = Counter()