Identifying Correlated Bots in Twitter
| Autor: | Nikan Chavoshi, Abdullah Mueen, Hossein Hamooni |
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| Rok vydání: | 2016 |
| Předmět: | |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783319478739 SocInfo (2) |
| Popis: | We develop a technique to identify abnormally correlated user accounts in Twitter, which are very unlikely to be human operated. This new approach of bot detection considers cross-correlating user activities and requires no labeled data, as opposed to existing bot detection techniques that consider users independently, and require large amount of recently labeled data. Our system uses a lag-sensitive hashing technique and a warping-invariant correlation measure to quickly organize the user accounts in clusters of abnormally correlated accounts. Our method is 94 % precise and detects unique bots that other methods cannot detect. Our system produces daily reports on bots at a rate of several hundred bots per day. The reports are available online for further analysis. |
| Databáze: | OpenAIRE |
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