Social Media Scraping for Analysis

Project Overview Implemented a Python script to extract posts, comments, and user interactions from multiple social media platforms to analyze trends and public sentiment.

Technical Challenges

• API Restrictions: Navigating through the limitations and rate limits of social media APIs.

• Data Volume: Handling large volumes of data efficiently to maintain performance.

Solutions Implemented

• API Utilization: Leveraged platform-specific APIs like Twitter API and Facebook Graph API for structured data access.

• Efficient Data Handling: Employed database systems and data caching to manage and store large datasets effectively.

Project Outcome The tool successfully gathers and aggregates social media data, enabling detailed sentiment analysis and trend monitoring which assists in market research and public relations strategies.

Technologies Used

• Languages: Python

• Libraries: Tweepy, Facebook-sdk, Pandas