Overall Behavioural Index (OBI) For Measuring Segregation

TL;DR

This paper introduces three novel segregation indexes, especially the Overall Behavioural Index (OBI), which provides a more nuanced measurement of segregation by considering individual and group connectivity behaviors, validated on real data.

Contribution

The paper proposes three new segregation indexes, including the OBI, which improves upon existing simplified measures by capturing detailed behavioral connectivity patterns.

Findings

OBI effectively captures complex segregation behaviors.

OBI outperforms baseline indexes on real CDR data.

New indexes provide nuanced insights into social segregation.

Abstract

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.