IIT Home Page CNR Home Page

A cognitive-based ego network detection system for mobile social networking

In future generation mobile systems information
about social networking structures of users will be fundamental,
being a key element for social networking applications, and a
crucial contextual information for personalising the behaviour of
mobile applications/services. In this paper, we focus specifically
on the detection of ego networks. They are networks formed
by an individual (ego) and all the other people she has a
social relationship with. We propose a completely decentralised
algorithm that allows each user’s mobile device to identify the
structure of its user’s ego network. The algorithm monitors
social interaction patterns between the ego and its peers. It
is completely decentralised and runs at each individual node
using local information only, scaling with the network size. it
does not disclose social interaction patterns, and it is able to
dynamically detect changes in the structure of the ego network,
being self-adaptive. The algorithm is based on social cognitive
heuristics, i.e. models about how the human brain groups social
relationships, described in the cognitive psychology literature.
Therefore, our approach reproduces - in users’ personal mobile
devices - the cognitive processes used by their human users to
understand their ego networks’ structure. We test it on real
datasets of interactions corresponding to (i) physical contacts and
(ii) exchange of information in online social networks. We show
that in both cases the detected social structures are remarkably
consistent with those described in the social sciences literature.
In addition, we study the dynamic behaviour of the algorithm,
highlighting how such structures evolve dynamically over time.


8th IFIP Wireless and Mobile Networking Conference (WMNC 2015), Munich, Germany, 2015

IIT authors:

Type: Article in proceedings of international peer-reviewed conference
Field of reference: Information Technology and Communication Systems

Activity: Future Internet
Social Networking