💬 InsightPulse

-By simply uploading a CSV file of reviews, the app instantly analyzes tone (Positive, Neutral, or Negative) and visualizes key trends through interactive charts.

-The name InsightPulse comes from the idea of feeling the pulse of user feedback:Capturing insights in real time to understand what users truly feel about a product.

🧠 Why I Built This

-During my 6th semester, I noticed how companies often collect tons of user feedback but struggle to interpret it quickly while something similar like this happened with me when i was conducting a workshop as GDG Cloud on campus Lead and got tons of feedback forms in a day and how difficult it was to organize the feedback and interpret the results

-So I built InsightPulse: A lightweight tool that translates raw text into data-driven insights within seconds.

🔹Problems InsightPulse Solves

-Scattered User Feedback: Companies collect thousands of reviews across platforms but struggle to quickly analyze what users actually feel.

-Slow Decision-Making: Product managers and consultants often rely on manual reading or external tools, delaying response to user sentiment trends.

-Lack of Actionable Insights: Traditional reports show data, not emotions — InsightPulse converts raw text into clear sentiment-driven insights.

-No Lightweight Solution: Existing analytics tools are complex or paid; InsightPulse is a simple, open-source solution that gives real-time understanding of customer mood.

🚀 Features

-Upload any CSV file containing a Review column

-Automatic Sentiment Detection (Positive / Neutral / Negative)

-Interactive Dashboard showing sentiment distribution

-Trend Insights highlighting sentiment changes over time

-Simple, clean Microsoft-style interface

💡 Working of InsightPulse

-Upload a CSV file containing customer reviews

-Each review is analyzed using TextBlob for sentiment polarity

-Sentiments are classified as Positive, Negative, or Neutral

-Dashboard displays metrics and bar charts for each sentiment group

-Provides quick, actionable insights for product and marketing teams

🛠️ Technologies Used

-Python – data processing & sentiment analysis

-Streamlit – interactive web app & dashboard

-Pandas – data handling and preprocessing

-TextBlob – natural language sentiment classification

-Matplotlib / Plotly – visualization of sentiment trends

⚙️ How to Run Locally

-Clone the repository: git clone https://github.com/Shriya-23/InsightPulse.git

-Navigate into the project: cd InsightPulse

-Install required libraries: pip install -r requirements.txt

Run the Streamlit app: streamlit run app.py

-Open the app in your browser → http://localhost:8501

💼 About Me

Hi! I’m Shriya Sharma,A Computer Science student passionate about building practical, data-driven solutions.

I enjoy creating simple, meaningful tools that connect technology, users, and real-world impact.