Update README.md

README.md

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-# Country-specific-Updated-Sentiment-Analysis-of-India
- Analyzing 5,000+ MEA India press releases using semantic matching via embeddings
-```mermaid
-flowchart TD
-    A[Start] --> B[Load CSV Data: Read mea_press_releases_1.csv]
-    B --> C[Preprocess Data:<br>- Convert date to datetime<br>- Combine title and description into combined_text<br>- Drop rows with missing values<br>- Extract year from date]
-    C --> D[Calculate Sentiment Scores:<br>- Initialize VADER Sentiment Analyzer<br>- Apply to combined_text for all rows]
-    D --> E[Extract Countries:<br>- Use spaCy NER to identify countries in combined_text<br>- Remove 'India' and 'New Delhi'<br>- Store as comma-separated strings in countries column]
-    E --> F[Get Unique Country Names from countries column]
-    F --> G[Generate Embeddings:<br>- Use SentenceTransformer to encode unique countries]
-    G --> H[Build FAISS Index with country embeddings]
-    H --> I[Input Query:<br>- Country name e.g., 'United States'<br>- Year threshold e.g., 2010]
-    I --> J[Encode Query Using SentenceTransformer]
-    J --> K[Find Similar Country Names:<br>- Search FAISS index for top k matches]
-    K --> L[Filter Data:<br>- Match countries column with similar names<br>- Keep rows where year >= threshold]
-    L --> M[Calculate Mean Sentiment per Year]
-    M --> N[Plot Mean Sentiment Over Years:<br>- Line plot with yearly averages]
-    N --> O[Plot Sentiment Over Time:<br>- Scatter plot with color-coded sentiments]
-    O --> P[Calculate and Print Average Sentiment]
-    P --> Q[End]
-   ```
+title: Country-specific-Updated-Sentiment-Analysis-of-India
+emoji: 🦀
+colorFrom: blue
+colorTo: yellow
+sdk: streamlit
+sdk_version: 1.42.2
+app_file: app.py
+pinned: false
+short_description: Analyzing 5,000+ MEA India press releases using semantic matching via embeddings
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+
+