Scrape Gab and collect: profile names, images, handles, status, shares, followers, region, views, posts, timestamp, likes, comments, groups, marketplace, members, organizations, and more.
Use Bright Data’s Web Scraper IDE,
or request a Gab dataset
Gab Scraper use cases
- Collect Gab comments on specific posts
- Scrape Gab to monitor brand awareness
- Find influencers with high social impact
- Analyze similar brands’ social media activity
Gab Scraper Overview
- Data scraping for beginners – easy to use
- Leveraging proprietary site unlocking technology
- Scalable – collect as many pages and profiles as you need at high speed
- Bright Data is fully committed to complying with all relevant data protection legal requirements, including GDPR and CCPA.
Web Scraper IDE Features
Pre-made web scraper templates
Built-in debug tools
Capture browser network calls, configure a proxy, extract data from lazy loading UI, and more!
Easy parser creation
Write your parsers in cheerio and run live previews to see what data it produced
You don’t need to invest in the hardware or software to manage an enterprise-grade web scraper
Emulate a user in any geo-location with built-in fingerprinting, automated retries, CAPTCHA solving, and more.
Built-in debug tools
Trigger crawls on a schedule or by API, and connect our API to major storage platforms
What you can do with the gab.com public data you scrape?
- Identifying influential users on gab.com by analyzing the frequency and reach of their posts and the engagement they receive from other users.
- Analyzing the language and terminology used on gab.com to understand the cultural and political beliefs and values of its users.
- Tracking changes in the topics and issues discussed on gab.com over time to understand what issues are important to its users and how their interests evolve.
- Using machine learning techniques to classify the sentiment of posts on gab.com and understand how users feel about different issues and topics.
- Developing and evaluating strategies for combating misinformation and fake news on gab.com by analyzing the spread and impact of false information on the platform.