AI Narrative Nexus - Dynamic Text Analysis Platform

NarrativeNexus is an end-to-end NLP-powered web application built using Streamlit that performs advanced text analysis on multiple document formats. It integrates text preprocessing, sentiment analysis, topic modeling, summarization, visualization, and automated reporting into a single interactive platform.

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Tech Stack

• Frontend/UI: Streamlit
• Backend: Python
• NLP Libraries: NLTK, Scikit-learn
• Deep Learning: Hugging Face Transformers
• Visualization: Matplotlib, WordCloud
• Reporting: ReportLab
• Data Handling: Pandas

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Project Architecture

NarrativeNexus/
│
├── app.py                  # Entry point
├── streamlit_ui.py         # UI rendering logic
├── collection.py           # File handling & text extraction
├── preprocessing.py        # Text preprocessing pipeline
├── cleaning.py             # Regex-based cleaning
├── sentiment.py            # Sentiment analysis (VADER)
├── model.py                # LDA topic modeling
├── summarization.py        # Extractive + Abstractive summarization
├── insights.py             # Insight generation
├── visualization.py        # Word cloud & charts
├── reporting.py            # PDF report generation
├── css.py                  # Custom UI styling
└── requirements.txt

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Workflow Pipeline

Input (Files/Text)
        ↓
Text Extraction
        ↓
Preprocessing (Clean → Tokenize → Lemmatize)
        ↓
Sentiment Analysis
        ↓
Topic Modeling (LDA)
        ↓
Summarization (Extractive + Abstractive)
        ↓
Insight Generation
        ↓
Visualization Dashboard
        ↓
Report Generation (PDF + CSV)

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Installation & Setup

1️⃣ Clone Repository
git clone https://github.com/Keerthana-webdev/Narrative-Nexus.git
cd NarrativeNexus

2️⃣ Install Dependencies
pip install -r
requirements.txt

3️⃣ Run Application
streamlit run app.py

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Usage

1. Upload files or paste text
2. Click "🚀 Analyze Text"
3. Explore:
   • Text statistics
   • Sentiment results
   • Topics
   • Summaries
   • Insights & visualizations
4. Download:
   • CSV output
   • PDF report

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Output Samples

• ✔ Sentiment classification with scores
• ✔ Topic keywords (LDA)
• ✔ Extractive & abstractive summaries
• ✔ Word cloud visualization
• ✔ Sentiment distribution charts
• ✔ Auto-generated PDF report

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Future Enhancements

• Real-time API integration
• Multi-language support
• Named Entity Recognition (NER)
• Keyword trend analysis

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Conclusion

NarrativeNexus demonstrates a complete NLP pipeline by combining classical machine learning and modern deep learning techniques into a scalable, user-friendly platform. It bridges the gap between raw text data and actionable insights.

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Author

Keerthana S