🧠 SentiMobile AI V3.5 | Neural Sentiment Engine

A Next-Gen Sentiment Analysis Dashboard designed with a Cyberpunk aesthetic. SentiMobile AI processes bulk customer reviews (CSV/Excel), extracts semantic insights, and visualizes data through an interactive, high-performance interface.

📸 Screenshots

• HomePage
• Loading
• ANALYSIS

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⚡ Key Features

🔍 Core Analysis

• Bulk Processing: Upload .csv or .xlsx files containing thousands of reviews.
• Sentiment Scoring: Polarity detection (Positive, Neutral, Negative) using NLP (TextBlob).
• Subjectivity Meter: Distinguishes between Factual statements and Opinionated text.
• Smart Sampling: Automatically extracts key review samples for each category (including edge cases).

📊 Advanced Visualization

• Cyber-Interface: A fully responsive, dark-mode UI with neon accents, particle animations, and glassmorphism.
• Timeline Analysis: Automatically detects dates to plot sentiment trends over time.
• Word Cloud: Generates a dynamic cloud of the most frequent keywords in the dataset.
• Interactive Charts: Powered by Chart.js (Pie, Line, and Bar charts).

🌐 User Experience

• Bilingual Support: One-click toggle between English and Arabic (RTL support).
• Flying Text Animation: Visualizes data processing in real-time during upload.
• Executive Abstract: AI-generated textual summary and strategic recommendations for Sellers & Buyers.

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🛠️ Tech Stack

• Backend: Python, Flask, Pandas, TextBlob.
• Frontend: HTML5, Tailwind CSS (CDN), Anime.js, Chart.js.
• Data Handling: Pandas, OpenPyXL.

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🚀 How to Run

1. Clone the repository:

   git clone [https://github.com/YourUsername/SentiMobile-AI.git](https://github.com/YourUsername/SentiMobile-AI.git)
   cd SentiMobile-AI

2. Install dependencies:

   pip install -r requirements.txt

3. Run the application:

   python app.py

4. Access the Dashboard: Open your browser and go to: http://127.0.0.1:5000

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📂 Project Structure

SentiMobile-AI/
│
├── app.py                 # The Flask Backend & Logic Core
├── requirements.txt       # Python Dependencies
├── README.md              # Documentation
│
├── templates/
│   └── index.html         # The Cyberpunk Frontend (Single File)
│
├── static/                # (Optional) For custom assets
│
└── Screenshots/           # Images for README
    ├── image.png
    └── ...

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📝 Data Formatting Guide

To ensure the best results, your uploaded file should follow these rules:

1. Format: .csv or .xlsx.
2. Review Column: Must contain a column named Review, Reviews, Text, Comment, or Body.
3. Date Column (Optional): If a date column exists (e.g., Date, Time), the system will generate a timeline chart.

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🔮 Future Roadmap

• Add deep learning models (BERT/RoBERTa) for higher accuracy.
• Implement color-coded Word Cloud based on sentiment.
• Export reports as PDF.

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Developed by KhalidExe © 2026