Tuesday, October 22, 2013

New Paper: Measuring Slum Severity in Mumbai and Kolkata

In a move to understand slums, we have switch gears slightly from agent-based modeling to a more statistical study of slums.  To this end we have just received word that our paper entitled "Measuring Slum Severity in Mumbai and Kolkata: A Household-based Approach" has just been Habitat International. Specifically we propose a new household level enumeration of slums and develop a Slum Severity Index as shown Table 4 below. Morover, the paper estimates number of slum households in Mumbai and Kolkata as shown in Figure 1 (below). Furthermore, the paper demonstrates that varying slum definitions result into stark differences in slum population estimates. Paper abstract:
"Slums pose a significant challenge for urban planning and policy as they provide shelter to a third of urban residents. UN-Habitat reports that, in 2001, approximately 924 million people lived in slums or informal settlements across the world (UN-Habitat, 2003). However, varying definitions of what constitutes a slum result in different slum population estimates. Most definitions treat a slum as a community of several households, rarely recognizing that housing conditions differ for each individual household within the area. Moreover, definitions of slums usually take a dichotomous approach whereby a place is either a slum or not. Little attempt is made to go beyond this slum/non-slum dichotomy. This paper moves beyond the traditional ways of defining a slum by proposing a new household level enumeration of slums and developing Slum Severity Index (SSI), which measures the level of deprivation on a continuous scale based on the UN-Habitat's slum definition. We apply this new approach of analyzing slums to a household survey dataset to estimate the total number of slum households in Mumbai and Kolkata, two megacities in India. To contrast our approach, we compare these estimates with the Census of India's. The comparison highlights stark differences in the two estimates and the slum/non-slum household classifications. The estimates by the Census are considerably smaller than those based on the UN-Habitat definition in both cities. By applying the SSI, we also demonstrate intra-urban variability in housing conditions within our study cities. The analysis highlights differences in slum profiles measured in terms of both housing deprivation levels and housing deprivation types in both cities. The main objective of this study is to demonstrate the usefulness of the household level analysis of slums in drawing implications for designing and implementing slum policies."
Keywords: Slums, Definition, Deprivation, India, Housing.

Full Reference: 
Patel, A., Koizumi, N. and Crooks, A.T. (2014), Measuring Slum Severity in Mumbai and Kolkata: A Household-based Approach, Habitat International, 41: 300-306. (pdf)
If you would like to read the paper and don't have access to Habitat International, feel free to send us an email and we can send you an early version of the paper.

Monday, October 21, 2013

IR: State-Driven and Citizen-Driven Networks

Our work exploring how social media can be used to study events around the world has resulted in a new publication in the  Social Science Computer Review entitled "International Relations: State-Driven and Citizen-Driven Networks." In essence what we are attempting to do is compare traditional international relations (e.g. from the United Nations General Assembly voting patterns) to those arising from the bottom up interactions (i.e from people on the ground). The abstract of the paper is below along with some of the images that accompany the paper.
The international community can be viewed as a set of networks, manifested through various transnational activities. The availability of longitudinal datasets such as international arms trades and United Nations General Assembly (UNGA) allows for the study of state-driven interactions over time. In parallel to this top-down approach, the recent emergence of social media is fostering a bottom-up and citizen driven avenue for international relations (IR). The comparison of these two network types offers a new lens to study the alignment between states and their people. This paper presents a network-driven approach to analyze communities as they are established through different forms of bottom-up (e.g. Twitter) and top-down (e.g. UNGA voting records and international arms trade records) IR. By constructing and comparing different network communities we were able to evaluate the similarities between state-driven and citizen-driven networks. In order to validate our approach we identified communities in UNGA voting records during and after the Cold War. Our approach showed that the similarity between UNGA communities during and after the Cold War was 0.55 and 0.81 respectively (in a 0-1 scale). To explore the state- versus citizen-driven interactions we focused on the recent events within Syria within Twitter over a sample period of one month. The analysis of these data show a clear misalignment (0.25) between citizen-formed international networks and the ones established by the Syrian government (e.g. through its UNGA voting patterns).

Full reference:
Crooks, A.T., Masad, D., Croitoru, A., Cotnoir, A., Stefanidis, A. and Radzikowski, J. (2013), International Relations: State-Driven and Citizen-Driven Networks, Social Science Computer Review. DOI:10.1177/0894439313506851 (pdf)
If you don't have access to Social Science Computer Review, send us an email and we can send you an early version of the paper. This is also only part of our work on using multiple networks to explore international relations. One can of course also explore the networks in more detail. For example in the figure below we plot the actual transfer of arms between states during the 2001 and 2011 period. One can clearly see how different states are connected with Syria however, Russia has connections to many states.

Arms transfers

Or if we explore Twitter hastags and add an edge between any pair of hashtags when they are used in the same tweet we can explore an emergent ontology of topic labels users associate with each other. For example, the #Allepo hashtag is associated with other hashtags which appear to local events, including “#civilian”, “#airstrike”, “#hunger”, “#pictures”, many of which are only connected to the #Aleppo hashtag as shown below.

Monday, October 07, 2013

Interurban Simulation Models

Following on from a previous post about the rise of civilizations. I thought it was worth blogging of another publication which I just came across in Environment and Planning A which demonstrates the utility of agent-based modeling for looking at urban systems by Denise Pumain and Lena Sanders. While I have blogged about the SimPop models before (here), which explore a systems of cities and how they evolve in space and time. In this recent paper the authors compare and contrast ABM with other styles of modeling. To quote from the paper:
"Agent-based models are increasingly used by urban specialists, supplanting the simulation models using differential equations which were more popular earlier. These models already made reference to the theories of self-organisation and to mechanisms of evolution not so far from those used today to describe the emergence of macroscopic properties or structures in a bottom-up process from interactions operating at the microlevel. Moreover there is less difference than often suggested in the literature between the two forms of modelling – differential equations and multi-agent models—in the way they integrate principles of urban theory. To test this assumption, we compare models made of systems of differential equations (Allen’s model firmly rooted in self-organisation theory and the model developed by Weidlich and Haag, affiliated to synergetic theory) with multi-agent models (SIMPOP family) designed to meet the same task: simulating the differentiated dynamics of urban entities over the medium to long term from their functional economic specialisation. We show that multi-agent systems are providing interesting solutions for the modelling method, because of their greater ability to simulate the emergence of geographical macro structures from different levels of interaction." 

Full Reference:
Pumain, D. and  Sanders, L. (2013). Theoretical principles in interurban simulation models: a comparison. Environment and Planning A, 45(9), 2243-2260.

The Rise of Civilizations

Have you ever wondered how today's societies have evolved the way they have? A recent paper by Peter Turchin and colleagues explores through a geographically explicit agent-based model such a question. To quote from the paper:
"How did human societies evolve from small groups, integrated by face-to-face cooperation, to huge anonymous societies of today? Why is there so much variation in the ability of different human populations to construct viable states? We developed a model that uses cultural evolution mechanisms to predict where and when the largest-scale complex societies should have arisen in human history. The model was simulated within a realistic landscape of the Afroeurasian landmass, and its predictions were tested against real data. Overall, the model did an excellent job predicting empirical patterns. Our results suggest a possible explanation as to why a long history of statehood is positively correlated with political stability, institutional quality, and income per capita."

Full Reference:
Turchin, P., Currie, T. E., Turner, E. A., and Gavrilets, S. (2013). War, space, and the evolution of Old World complex societies. Proceedings of the National Academy of Sciences, 201308825.