each data row contains the description of a single person, e.g., of a customer, an employee, a politician, a friend.
Similarities between people can be related to vicinity, similarity of interests, similarity of buying patterns, frequency
of email or telephone exchanges, etc.
Objectives of data mining and visualization:
To analyze relationships between different people in the social networks
To filter the social network nodes (by using parallel coordinates) depending on coordinates associated to the different people
To focus on the individual social network around a person while at the same time visualizing the complete context
(the entire social network) on demand, possibly ad different levels of resolution
LIONoso sample visualization(s): Focus and context navigation
In the example image one visualizes a social network given by politicians, the name and image of the person is associated to an orb.
By double-clicking on the orb one visualizes only the people connected to the selected person. In this specific case a connections
and the physical vicinity of two orbs is related to the frequency with which two politicians signed law proposal together in the
last years. The original data are related to analyzing the network of politicians in a manner similar to the way in which Google
and other search engines analyze a network of web pages (pagerank, hubness, authority values, etc.).