Update app.py

app.py

@@ -6,7 +6,7 @@ from transformers import pipeline
 import plotly.graph_objects as go
 
 # Load the sentiment analysis model
-pipe = pipeline("text-classification", model="pramudyalyza/bert-indonesian-finetuned-news")
+pipe = pipeline("text-classification", model="pramudyalyza/bert-indonesian-finetuned-news-v2")
 
 # Function to process the keyword and get sentiment analysis
 def process_keyword(keyword):
@@ -29,9 +29,10 @@ def process_keyword(keyword):
 
     positive_count = (df_clean['sentiment'] == 'Positive').sum()
     negative_count = (df_clean['sentiment'] == 'Negative').sum()
+    neutral_count = (df_clean['sentiment'] == 'Neutral').sum()
     total_count = len(df_clean)
 
-    return positive_count, negative_count, total_count, df_clean
+    return positive_count, negative_count, neutral_count, total_count, df_clean
 
 # Streamlit app layout
 st.title("News Sentiment Analysis Dashboard")
@@ -41,7 +42,7 @@ keyword_input = st.text_input("Enter a keyword to search for news", placeholder=
 if st.button("Analyze"):
     if keyword_input:
         with st.spinner('Scraping and analyzing the data...'):
-            positive_count, negative_count, total_count, df_clean = process_keyword(keyword_input)
+            positive_count, negative_count, neutral_count, total_count, df_clean = process_keyword(keyword_input)
 
         # Create plots
         fig_positive = go.Figure(go.Indicator(
@@ -60,11 +61,19 @@ if st.button("Analyze"):
                    'bar': {'color': "red"}}
         ))
 
+        fig_neutral = go.Figure(go.Indicator(
+            mode="gauge+number",
+            value=neutral_count,
+            title={'text': "Neutral Sentiment"},
+            gauge={'axis': {'range': [0, total_count]},
+                   'bar': {'color': "yellow"}}
+        ))
+
         fig_donut = go.Figure(go.Pie(
-            labels=['Positive', 'Negative'],
-            values=[positive_count, negative_count],
+            labels=['Positive', 'Negative', 'Neutral'],
+            values=[positive_count, negative_count, neutral_count],
             hole=0.5,
-            marker=dict(colors=['green', 'red'])
+            marker=dict(colors=['green', 'red', 'yellow'])
         ))
         fig_donut.update_layout(title_text='Sentiment Distribution')
 
@@ -74,7 +83,9 @@ if st.button("Analyze"):
         # Display results in each column
         col1.plotly_chart(fig_positive, use_container_width=True)
         col2.plotly_chart(fig_negative, use_container_width=True)
-        col3.plotly_chart(fig_donut, use_container_width=True)
+        col3.plotly_chart(fig_neutral, use_container_width=True)
+
+        st.plotly_chart(fig_donut, use_container_width=True)
 
         st.write(f"News articles found: {total_count}")