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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Detecting and Analyzing Automated Activity on Twitter
verfasst von : Chao Michael Zhang, Vern Paxson
Erschienen in: Passive and Active Measurement
Verlag: Springer Berlin Heidelberg
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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.