This article discusses approaches to collecting data from Web 2.0 platforms such as social networks and messengers. The authors propose the implementation of a flexible architecture for a focused web crawler to collect data of users’ discussion in the social network Facebook and the Telegram messenger. The proposed crawler is based on interaction with a platform’s API, get/post requests, and simulating actions in a browser. The authors set up an experiment comparing implementation of proposed data crawling approaches. The data on the COVID-19 virus was collected from Facebook social network and Telegram messenger using RUM Extractor for Facebook and large number open-source Telegram crawler. Developed focused crawler reached the speed of 15 participants per second and 12 posts per second without blocking account when processing a user discussion in Facebook. Telegram crawler showed the speed of 200 participants per second and 300 posts per second without blocking.