Sentiment Analysis Using Google Search

Google Search results scraper combined with NLP-based sentiment analysis using the Piloterr Google Search API.

This project focuses on:

• Extracting real-time search results from Google
• Calculating sentiment scores (negative, neutral, positive, compound) for each snippet
• Preparing structured data for further visualization or reporting (visualization is not included in this repo)

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Clone the project

git clone https://github.com/harivonyR/Sentiment_analysis_using_Google_search/
cd Sentiment_analysis_using_Google_search

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Configure your API key

Edit the credentials file:

cd credential.example
nano credential.py

Replace the placeholder with your Piloterr API Key.
You can request a key from Piloterr.com.

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Install dependencies

Core (development):

pip install pandas requests os

NLP Models:

pip install scipy transformers torch

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Run the main script

python main.py

This will:

1. Scrape Google search results for your chosen keyword
2. Calculate sentiment scores for each row in the dataset
3. Return the results as dataframe for your own analysis and visualization

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💡 *Explore the full analysis with data visualisation on Google Colab : Sentiment analysis using Piloterr Google Search API and NLP.