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yesterday by fozbaca
Research: "Don't @ Me: Hunting Twitter Bots at Scale"
New research from Duo Labs focusing on identifying Twitter bots at scale discusses ways of effectively identifying bots on Twitter, with Duo researchers applying their approach in a "case study" analysis focusing on a botnet spreading a cryptocurrency scam. Duo first identified a dataset of 88 million public Twitter accounts for the study, and then utilized "practical data science techniques" to find the bot networks.  Duo says that "by monitoring the botnet over time, we discover ways the bots evolve to evade detection," adding that "after finding initial bots using the tools and techniques described in this paper, a thread can be followed that can result in the discovery and unraveling of an entire botnet." Duo notes that their research is focused purely on identifying automated Twitter accounts, as opposed to automated accounts that are "necessarily malicious."

Duo made the data collection code they used open source; it's available on GitHub.

Read the full technical paper (pdf) here.
research  twitter  social  bot  botnet  bots  duo 
yesterday by dmcdev

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