The Network Coincidence Analysis project’s aim is to integrate traditional statistical techniques with automatic learning and social network analysis tools for the purpose of obtaining visual and interactive displays of big data. The interdisciplinary team involved has the following objectives:
- Efficiently combine different statistical techniques by integrating them under the study of the coincidence of people, objects, events or characteristics in a multiple series of scenarios;
- Design open-source software that under the premise of network coincidence analysis generates different types of interactive graphics that enable an exploratory and confirmatory analysis to be made of vast quantities of information, and
- Apply all the above to the creation and handling of large databases in such diverse fields as the following:
a) Survey data combined with administrative data,
b) The analysis of networks created by Twitter users and those reproduced through their messages,
c) The abstracts of scientific output in different disciplines over long periods of time through the generation of semantic maps, and
d) The creation of a huge database of leading figures in the fields of philosophy, science, social sciences and the arts, which also contains their major works, and which involves resorting to, among other sources, the public data records of libraries and museums.