13 June 2017
San Francesco - Via della Quarquonia 1 (Classroom 1 )
Inspired by its biological counterpart, we'll introduce the concept of
digital DNA, as a mechanism to characterize online user behaviors on
social media and the Web. We'll model online users' actions as digital
DNA sequences, introducing a strikingly novel, simple, and effective
approach to model and analyze different types of online accounts. The
high flexibility featured by digital DNA sequences, makes this modeling
technique well suited for different scenarios, with the potential to
open up new directions for research. It also opens up the possibility to
draw upon decades of research and development in bioinformatics.
Among the possible applications, it will be presented a series of
experiments in which digital DNA has been successfully used to detect
Twitter spambots. In particular, a spambot detection techniques able to
provide an effective mean to detect novel, evolving social spambots on
Twitter. An extensive investigation, leveraging a wide experimental
campaign, shows that neither Twitter, nor humans, nor cutting-edge
applications are currently capable of accurately detecting such novel
social spambots. Instead, this digital fingerprinting detection
technique, based on the DNA-like sequentialization approach, succeeds in
revealing the novel spambots, in an unsupervised fashion and only
exploiting the timeline data, thus being both effective and efficient.
relatore:
Spognardi, Angelo
Units:
SysMA