Localising social network users and profiling their movement

Profiling Social Network Users With Machine Learning

Social Networks are becoming increasingly popular in our daily communication and rapid developments in data gathering technology have led to large amounts of data that are available from users’ interactions. On the other side, the complexity of analyzing social interactions is not related only to the size of the network to be analyzed, but also to the nature of the interactions. One of the most...

Authenticating users through their arm movement patterns

In this paper, we propose four continuous authentication designs by using the characteristics of arm movements while individuals walk. The first design uses acceleration of arms captured by a smartwatch’s accelerometer sensor, the second design uses the rotation of arms captured by a smartwatch’s gyroscope sensor, third uses the fusion of both acceleration and rotation at the featurelevel and f...

Multiple Location Profiling for Users and Relationships from Social Network and Content

Users’ locations are important for many applications such as personalized search and localized content delivery. In this paper, we study the problem of profiling Twitter users’ locations with their following network and tweets. We propose a multiple location profiling model (MLP), which has three key features: 1) it formally models how likely a user follows another user given their locations an...

Multiple Location Profiling for Users and Relationships from Social Network and Content

Making privacy personal: Profiling social network users to inform privacy education and nudging

Social Network Sites (SNSs) offer a plethora of privacy controls, but users rarely exploit all of these mechanisms, nor do they do so in the same manner. We demonstrate that SNS users instead adhere to one of a small set of distinct privacy management strategies that are partially related to their level of privacy feature awareness. Using advanced Factor Analysis methods on the self-reported pr...