Data Mining Has Revealed Previously Unknown Russian Twitter Troll Campaigns
Trolls left forensic fingerprints that cybersecurity experts used to find other disinformation campaigns both in the US and elsewhere
By Emerging Technology from the arXiv
Human activity leaves all kinds of traces, some more obvious than others. For example, messages posted to services such as Twitter are obviously visible. But the pattern of tweets from a user over time is not as self-evident.
Various researchers have begun to study these patterns and found that they can identify certain types of accounts, particularly those that post in high volume. For example, accounts that post continuously, 24 hours a day, are unlikely to be operated by humans. Instead, this is a clear signal that a bot of some kind is at work.
Humans also generate specific patterns, albeit less obviously than bots. In particular, accounts that post high volumes of tweets often do so in a pattern whose unique signature forensic analysis can identify.
One corpus of interesting tweets encompasses the messages posted by Russian trolls attempting to influence the 2016 US presidential election. Now researchers have analyzed these to search for any unique…
