What question did this study set out to answer?

The aim is to develop a real-time system for detecting suspicious URLs in tweets to enhance cybersecurity measures.

WarningBird: A Near Real-Time Detection System for Suspicious URLs in Twitter Stream

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Randomized trial demonstrates efficient detection of suspicious URLs in Twitter streams, indicating improved security measures.

The aim is to develop a real-time system for detecting suspicious URLs in tweets to enhance cybersecurity measures.
Developed a detection system called WARNINGBIRD focusing on URL redirect chains from tweets.
Collected tweets from the Twitter public timeline for analysis.
Built a statistical classifier to evaluate the suspiciousness of URLs based on collected data.
The classifier accurately detects suspicious URLs with high efficiency.
Demonstrated that correlated URL redirect chains effectively indicate suspicious activity.

Lee et al. (2013) studied this question.

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