Abstract. We present a method for determining whether a Twitter account exhibits automated behavior in publishing status updates known as tweets. The approach uses only the publicly available timestamp information associated with each tweet. After evaluating its effectiveness, we use it to analyze the Twitter landscape, finding that 16% of active accounts exhibit a high degree of automation. We also find that 11% of accounts that appear to publish exclusively through the browser are in fact automated accounts that spoof the source of the updates.
Zhang et al. REF proposed a method for detecting instances of automated Twitter accounts using the publicly available timestamp associated with each tweet.
Detecting and analyzing automated activity on twitter
In Proceedings of the 12th International Conference on Passive and Active Measurement (PAM’11
Computer Science