Qriton Scales Disinformation Analysis to 2M Records Using Apify
▶ The 2-minute explainer
Summary
Qriton successfully scaled its election disinformation analysis to process 2 million records by utilizing Apify, a web scraping and automation platform. This case study details a six-platform crawl that uncovered coordinated influence campaigns related to Armenia's 2026 election.
Why it matters
Professionals in data science, cybersecurity, and public relations need to understand how advanced scraping and analysis tools can be used to detect and combat large-scale disinformation campaigns, which can impact brand reputation, market stability, and democratic processes.
How to implement this in your domain
- 1Evaluate web scraping tools like Apify for large-scale data collection needs.
- 2Develop strategies for identifying and monitoring potential disinformation sources relevant to your industry.
- 3Implement automated data pipelines for continuous monitoring and analysis of online content.
- 4Train teams on identifying patterns of coordinated influence and misinformation.
- 5Collaborate with data ethics experts to ensure responsible data collection and usage.
Who benefits
Key takeaways
- Qriton used Apify to scale disinformation analysis to 2 million records.
- The project focused on coordinated influence around Armenia's 2026 election.
- Web scraping and automation platforms are crucial for large-scale data collection.
- This demonstrates practical application in combating election disinformation.
Original post by Natasha Lekh
"Inside the six-platform crawl that exposed coordinated influence around Armenia's 2026 election."
View on XOriginally posted by Natasha Lekh on X · view source
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