The German foreign ministry, which commissioned the study after suspecting it was being targeted by bots, said the findings highlighted the need for governments to systematically tackle the growing number of disinformation campaigns and recognise the effect they could have on elections.
Democratic countries are so far behind in this kind of asymmetrical information war. The Kremlin and now also CCP have been blasting propaganda and bad information on social media for years, and democracies are still flat footed.
How is that supposed to look?
How do you differentiate legit free speech, from concerted propaganda efforts? Especially as information is very volatile nowadays. How do you mark false information, without creating systems abused to opress investigative exposures and whistle blowers?
Russia and China dont need to protect free speech, press and information.
Social Networks have more meta information than you see on their frontend. It would be possible for them to find those networks based on who they follow, retweet, like and engage with. Or maybe check if they only write in German, but only post during business hours in St. Petersburg …
St. Petersburg is just two hours earlier in winter and one hour earlier in sommer bc. of summer time.
It is very difficult to acertain a single user to be a “bot” either as a true machine program or as a paid troll. By those metrics you can observe larger efforts. E.g. is the spread of time windows of certain accounts, which write for a specific point and argument significantly different from the overall users that engage with this kind of topic?
Is there a specific pattern how many accounts interact with specific topics, e.g. are they always “first on the scene”?
But for an individual account it is quite difficult to identify. Could be that it is just one person getting up early. Could be that this person loves to tweet over his morning coffee.
I can highly recommend this presentation on The Rise and Fall of “Social Bot” research where the presentator concluded most metrics to be used in research until then to be arbitrary and giving many examples of real users that were considered as bots by those poor metrics. It is from the end of 2021, so i assume the research has improved in the past 2 years.
The key takeway remains though. There is no simple way to identify individual accounts as “bots”.
Time zone is just one indicator that doesn’t says much by itself. However if you have a handful of indicators, it becomes easier to positively identify bots.
Fraud detection for online shops works in a similar way, where they check your location, IP, delivery address and other metrics to assign a risk score to each order.
Yeah, it’s a major disadvantage for countries with more freedom. Some obvious steps would be public information campaigns and working with and regulating social media companies.
But those aren’t easy solutions, especially since the Kremlin has an asset running for US president trying to divide the country and weaken it’s support for other democracies.