Update src/streamlit_app.py

src/streamlit_app.py

@@ -51,7 +51,7 @@ else:
     st.warning("No reviews match the selected filters.")
 
 # Top complaint words
-st.subheader("Top Complaint Words")
+st.subheader("Key Complaint Drivers")
 
 negative_reviews = filtered_df[filtered_df["sentiment"] == "negative"]["review_text"]
 
@@ -64,10 +64,16 @@ if len(negative_reviews) > 0:
         "a", "an", "this", "that", "with", "on", "at", "my", "our", "we",
         "i", "had", "but", "very", "so", "not", "be", "been", "are", "as",
         "they", "them", "you", "he", "she", "his", "her", "their", "there",
-        "here", "have", "has", "from", "too", "all"
+        "here", "have", "has", "from", "too", "all",
+        "will", "would", "back", "one", "get", "got", "go", "went",
+        "also", "even", "still", "really", "just", "make", "made",
+        "time", "day", "thing", "things", "place"
     }
 
-    filtered_words = [word for word in words if word not in stopwords and len(word) > 2]
+    filtered_words = [
+        word for word in words 
+        if word not in stopwords and len(word) > 3
+    ]
 
     if filtered_words:
         word_counts = Counter(filtered_words).most_common(10)
@@ -76,7 +82,7 @@ if len(negative_reviews) > 0:
     else:
         st.info("No meaningful complaint words found.")
 else:
-    st.info("No negative reviews available for this selection.")
+    st.info("No negative reviews available.")
 
 # Example reviews
 st.subheader("Example Customer Reviews")