GUI Programming with Python: QT Edition by Rempt B.

By Rempt B.

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Information loss [17] checks the quantity of data that has been harmed during the protection process and therefore is no longer useful. Disclosure risk [6][21][22] measures the quantity of original data that can be discovered through the protected data. The remaining of this paper is structured as follows. In Section 2 we explain the methodology followed to go from a real social network like Twitter to obtaining a microdata dataset with explicit and implicit information about users. Section 3 contains the description of the protection method used in this work to protect the microdata dataset: the microaggregation.

2 User Profiles Generation The second step to do is to use the data structures collected by the crawler in order to get a profile for each user containing his location, his connected users and, his three most relevant topics of interest. In order to do this it should be noticed that information is not always explicitly given in the social networks. That is, using the Twitter API we can get the location but it is not possible to get the topics that a user is interested about because they are not specified nor described anywhere.

This lack of possible operations makes the protection a difficult task. Protection methods are typically evaluated using two measures: information loss and disclosure risk. Information loss [17] checks the quantity of data that has been harmed during the protection process and therefore is no longer useful. Disclosure risk [6][21][22] measures the quantity of original data that can be discovered through the protected data. The remaining of this paper is structured as follows. In Section 2 we explain the methodology followed to go from a real social network like Twitter to obtaining a microdata dataset with explicit and implicit information about users.

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