CARLEY, Kathleen M.

LIN JUNJIE, LARRY,

Institutional Knowledge at Singapore Management University

Singapore Management UniversityInstitutional Knowledge at Singapore Management UniversityResearch Collection School Of Information Systems School of Information Systems7-2016Response to SBP-BRiMS Data Challenge: Agent-based approach to human migration movementLIN JUNJIE, LARRYSingapore Management University, larry.lin.2013@phdis.smu.edu.sgKathleen M. CARLEYFollow this and additional works at: https://ink.library.smu.edu.sg/sis_researchPart of the Computer Sciences Commons, and the Sociology CommonsThis Conference Paper is brought to you for free and open access by the School of Information Systems at Institutional Knowledge at SingaporeManagement University. It has been accepted for inclusion in Research Collection School Of Information Systems by an authorized administrator ofInstitutional Knowledge at Singapore Management University. For more information, please email libIR@smu.edu.sg.CitationLIN JUNJIE, LARRY and CARLEY, Kathleen M.. Response to SBP-BRiMS Data Challenge: Agent-based approach to humanmigration movement. (2016). 2016 International Conference on Social Computing, Behavioral-Cultural Modeling , & Prediction andBehavior Representation in Modeling and Simulation (SBP-BRiMS’16). Research Collection School Of Information Systems.Available at: https://ink.library.smu.edu.sg/sis_research/3316Response to SBP-BRiMS Data Challenge:Agent-Based Approach to Human MigrationMovementLarry Lin1 and Kathleen M. Carley21 Singapore Management University, School of Information Systems,Living Analytics Research Centre, 80 Stamford Road, Singapore 178902larry.lin.2013@phdis.smu.edu.sg2 Carnegie Mellon University, School of Computer Science,Institute for Software Research, 5000 Forbes Avenue, Pittsburgh, PA 15213kathleen.carley@cs.cmu.edu1 Social Question and ImportanceIn this work, we attempt to address the social question of international migration,and the resulting shifts in country populations. This is achieved through thedevelopment of a country-level agent-based dynamic network model to examineshifts in population given network relations among countries, which influencesoverall population change.The importance of this social question is substantiated by recent trends.With trends indicating a new world makeup in terms of shifts in population[1], this presents tremendous opportunities and risks. It becomes imperative tounderstand the dynamics involved in migration through the development of amodel that is sensitive to real-world trends, and serves as a reasoning platformfor changes in migration policies amongst countries.2 Novel ContributionThe first contribution of this paper would be the development of country net-works that were incorporated into the agent migration decision model, rangingfrom alliances to linguistic similarity to economic disparity networks. To the bestof our knowledge, previous works in migration do not consider such a wide rangeof country networks for the migration decision model. We believe that this wouldresult in a more realistic model that is sensitive to real-world trends.The next major contribution would be incorporation of age distributions (re-fer to figure 1 (b)) of countries, which are initialized with actual data, and thenshifted as a result of births, deaths and migration. Through the incorporationof this feature, it allows policy makers to be able to observe shifts in age distri-butions of countries, and make informed decisions regarding migration policies.In the future, we could even make use of the age distributions in developmentof intelligent agents, whereby countries could change their migration policiesaccording to certain trends that is observed in the age distributions.2 Agent-Based Approach to Human Migration Movement3 Data Sets and MethodologyKey methodology is the use of a country-level agent-based dynamic networkmodel to examine shifts in population given network relations among countries,which influences overall population change. A total of 6 country networks weredeveloped using multiple data sources. The networks includes alliance and hos-tility (developed using GDELT data and CAMEO scale [3]), linguistic similarity(common language), proximity (distance), sea-level (percent of population below5 meters [2]), economic influence (i.e. GDP [2]) and migrant networks [4], wheremigrants in a destination country have a positive externality effect on futuremigrants from the same origin country.Figure 1 (a) shows the interface of the model that was developed.Fig. 1. On left: (a) Age distribution, which is initialized using actual data. Age distri-butions for non-migrants (native) and migrants of a country are shown in blue and redrespectively. Shifts are introduced through migration, fertility and mortality. On right:(b) Interface of model developed using NetLogo 3D 5.2.0. User is able to select countryof origin for displaying the flow of migrants. Red to yellow to green lines indicate highto medium to low flow of migrants respectively.Validation of the flow probabilities between (top 20 populous) countries areas shown in figure 2. From the plot, we can observe how close are the actual andsimulated migration probabilities.Fig. 2. Migration probabilities (between top 20 populous countries) as heat maps: (left)actual migration probabilities, (right) simulated migration probabilities.Agent-Based Approach to Human Migration Movement 34 AcknowledgementsThis research is supported by the National Research Foundation, Prime Min-ister’s Office, Singapore under its International Research Centres in SingaporeFunding Initiative.References1. Baer, D, 2015. ’The biggest change of our time’ is happeningright now in Africa. Retrieved from: http://www.techinsider.io/africas-population-explosion-will-change-humanity-2015-82. World Bank, 2016. ’Open Data’. Retrieved from: http://data.worldbank.org/3. CEDS, 2012. Computational Event Data System: CAMEO Event Data Codebook.Retrieved from: http://eventdata.parusanalytics.com/data.dir/cameo.html4. United Nations, 2015. International Migration Stock 2015. Retrieved from:http://www.un.org/en/development/desa/population/migration/data/estimates2/estimates15.shtml

Response to SBP-BRiMS Data Challenge: Agent-based approach to human migration movement

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Response to SBP-BRiMS Data Challenge: Agent-based approach to human migration movement

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