On the Protection of Social Network-Extracted Categorical Microdata

Social networks have become an essential part of the people?s communication system. They allow the users to express and share all the things they like with all the people they are connected with. However, this shared information can be dangerous for their privacy issues. In addition, there is some information that is not explicitly given but is implicit in the text of the posts that the user shares. For that reason, the information of each user needs to be protected. In this paper we present how implicit information can be extracted from the shared posts and how can we build a microdata dataset from a social network graph. Furthermore, we protect this dataset in order to make the users data more private. URL http://link.springer.com/chapter/10.1007/978-3-642-36074-9_4#page-1 [7] Source URL: https://www.iiia.csic.es/en/node/54278 Links [1] https://www.iiia.csic.es/en/staff/jordi-mar%C3%A9s [2] https://www.iiia.csic.es/en/staff/vicen%C3%A7-torra [3] https://www.iiia.csic.es/en/bibliography?f[author]=446 [4] https://www.iiia.csic.es/en/bibliography?f[keyword]=497 [5] https://www.iiia.csic.es/en/bibliography?f[keyword]=498 [6] https://www.iiia.csic.es/en/bibliography?f[keyword]=496 [7] http://link.springer.com/chapter/10.1007/978-3-642-36074-9_4#page-1