Christos Perentis

TL;DR: The proposed methodology could have a societal impact opening the way to customized mobile phone applications, which may detect and suggest to the user specific actions in order to prevent disease spreading and minimize the risk of contagion.

TL;DR: My Data Store is presented, a tool enabling people to control and share their personal data and preliminary results show improvement over the users' awareness of theirpersonal data and the perceived usefulness of the tool.

TL;DR: Analysis of factors affecting users’ choices toward the disclosure of their personal data, including not only their demographic and self-reported individual characteristics, but also their social interactions and their mobility patterns inferred from months of mobile phone data activity shows that social interaction inferred by mobile phones is an important factor revealing willingness to share.

TL;DR: It is shown that auxiliary information from the user-item network fruitfully combines with the friendship network to enhance friend recommendations and the proposed method is more accurate in recommending friends when compared with two single source path-based algorithms using both synthetic and real data sets.

TL;DR: In this paper, the authors investigate the factors affecting users' choices toward the disclosure of their personal data, including not only their demographic and self-reported individual characteristics, but also their social interactions and their mobility patterns inferred from months of mobile phone data activity.