  Segregation, defined as the degree of separation between two or more
population groups, helps to understand a complex social environment and
subsequently provides a basis for public policy intervention. To measure
segregation, past works often propose indexes that are criticized for being
over-simplified and over-reduced. In other words, these indexes use the highly
aggregated information to measure segregation. In this paper, we propose three
novel indexes to measure segregation, namely: (i) Individual Segregation Index
(ISI), (ii) Individual Inclination Index (III), and (iii) Overall Behavioural
Index (OBI). The ISI index measures individuals' segregation, and the III index
reports the individuals' inclination towards other population groups. The OBI
index, calculated using both III and ISI index, is non-simplified and not only
recognizes individuals' connectivity behaviour but group's connectivity
behavioural distribution as well. By considering commonly used Freeman's
segregation and homophily index as baseline indexes, we compare the OBI index
on real call data records (CDR) dataset of Estonia to show the effectiveness of
the proposed indexes.
