“Hiding individuals and communities in a social network” is an article published in the Nature Human Behaviour magazine. Dr. Tomasz Michalak from the Faculty of Mathematics, Informatics and Mechanics of the University of Warsaw is among its authors.

 

Social media has fuelled enormous interest in developing evermore sophisticated tools to analyse our personal connections, with a particular emphasis on detecting communities and identifying key individuals in a social network. Such tools raise privacy concerns as they may be used to reveal private information.

 

In the article entitled “Hiding individuals and communities in a social network” scientists ask whether people can actively manage their connections to evade such tools. By addressing this research question, the general public may better protect their privacy, oppressed activist groups may better conceal their existence, and security agencies may better understand how terrorists escape detection. The authors study how individuals can evade “node centrality” analysis without compromising their influence. They prove that an optimal solution to this problem is hard to compute. Despite this hardness, the scientists demonstrate how even a simple heuristic, whereby attention is restricted to the individual’s network neighbourhood, can be surprisingly effective in practice, e.g., it could easily disguise Mohamed Atta’s leading position within the WTC terrorist network. They also study how a community can increase the likelihood of being overlooked by community-detection algorithms. The authors demonstrate the effectiveness of a heuristic whereby members of the community either “unfriend” certain individuals or “befriend” certain others, in a coordinated effort to camouflage their community.

 

The authors of the article: Dr. Marcin Waniek (Masdar Institute of Science and Technology, UAE), Dr. Tomasz Michalak (Faculty of Mathematics, Informatics and Mechanics, UW), Prof. Michael Wooldridge (Department of Computer Science, Oxford University), Dr. Talal Rahwan (Masdar Institute of Science and Technology, UAE).

Hiding individuals and communities in a social network >>