| Abstract: |  This bachelor project concerns analysis of sensitive information propagation in
social networks. After reading through the present problematic of information
propagation and privacy protection on social networks, a model and metrics
were made with emphasis on potentially sensitive information. One of them is
inovative model based on user interaction. It is assumed, that people that
show interest in an information, for example by leaving a comment, would
likely spread the information.
During the creation of the application for validating the model on Facebook
platform an interesting fact was found, that to implement suggested techniques
it would be required much bigger access to users data, than is allowed by
standard API. The final application consists of mechanisms, that
analyze information propagation in given environment. In order to analyse
the model it was needed to extract data from all users of the application and
process them.
Unfortunately the dataset size was too small, but after all it was capable of
testing the model and propose where to turn the future research.
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