3 ms·
There are a lot of heuristics Twitter could use to estimate likelihood of bot accounts: 1) Source IP range + number of accounts linked 2) interaction speed (s
by sangnoir 5y ago
There are a lot of heuristics Twitter could use to estimate likelihood of bot accounts:
1) Source IP range + number of accounts linked
2) interaction speed (some actions are too fast to be human, or show coordination like tweeting exact same tweet as a different account withing .2 seconds)
3) interaction times in a rolling window (individual humans need sleep, and usually around the same time)
4) IP packet fingerprinting: can flag discrepancies like a client seemingly tweeting from "Twitter for iPhone" but originating from a Linux/*BSD/windows host
- maharajatever 5y agoIsn't it really amazing that no malicious bot author thought about these before...
- sangnoir 5y agoI'm sure they have, but not all of them have the means (and time) to bypass some of the measures, defeating single-source-IP[1] bots and script-kiddies can cut down on the amount of bots. It's an arms-race that I've fought on both sides of: deploying anti-abuse measures and writing a very well-behaved scraper; unfortunately some sites block all scrapers despite their behavior, and you have to figure out how the detection is done empirically and enjoy your short-lived victories while they last. On the defensive side, you continually have to update your detection heuristics, and the short-lived victories. 1. I also have a read-only Twitter archiving bot that doesn't hide its nature (the handle is "${NOUN}bot"). It runs from a single VPS at regular cron intervals. It'd be trivial for Twitter to detect this and make it not worth my while.