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March  2015, 10(1): 87-99. doi: 10.3934/nhm.2015.10.87

Characterizing ethnic interactions from human communication patterns in Ivory Coast

1. 

Grupo de Sistemas Complejos, Universidad Politécnica de Madrid, ETSI Agrónomos, 28040, Madrid, Spain

2. 

Departamento de Electrónica, Universidad Técnica Federico Santa María, Av. España 1680, Valparaíso

3. 

Grupo de Sistemas Complejos, Universidad Politécnica de Madrid, ETSI Agrónomos, 28040, Madrid, Spain

4. 

Grupo de Sistemas Complejos, Universidad Politécnica de Madrid, ETSI Agrónomos, 28040, Madrid, Spain, Spain

Received  July 2014 Revised  December 2014 Published  February 2015

Towards the consolidation of peace and national development, Ivory Coast must overcome the lack of cohesion, responsible for the emergence of two civil wars in the last years. As in many African countries, ethnic violence is a result of the way territories are organized and the prevalence of some groups over others. Nowadays the increasing availability of electronic data allows to quantify and unveil societal relationships in an unprecedented way. In this sense, the present work analyzes mobile phone data in order to provide information about the regional and ethnic interactions in Ivory Coast. We accomplish so by means of the construction and analysis of complex social networks with several types of interactions, such as calling activity and human mobility. We found that in a subregional scale, the ethnic identity plays an important role in the communication patterns, while at the interregional scale, other factors arise like economical interests and available infrastructure.
Citation: Alfredo Jose Morales, Werner Creixell, Javier Borondo, Juan Carlos Losada, Rosa Maria Benito. Characterizing ethnic interactions from human communication patterns in Ivory Coast. Networks & Heterogeneous Media, 2015, 10 (1) : 87-99. doi: 10.3934/nhm.2015.10.87
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A. J. Morales, J. Borondo, J. C. Losada and R. M. Benito, Efficiency of human activity on information spreading on Twitter,, Social Networks, 39 (2014), 1.  doi: 10.1016/j.socnet.2014.03.007.  Google Scholar

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T. Sakaki, M. Okazaki and Y. Matsuo, Earthquake shakes twitter users: Real-time event detection by social sensors,, Proceedings of the 19th International Conference on World Wide Web (New York, (2010), 851.  doi: 10.1145/1772690.1772777.  Google Scholar

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J. L. Toole, M. Ulm, M. C González and D. Bauer, Inferring land use from mobile phone activity,, in Proceedings of the ACM SIGKDD International Workshop on Urban Computing, (2012), 1.  doi: 10.1145/2346496.2346498.  Google Scholar

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, =, ().   Google Scholar

show all references

References:
[1]

, Annual Report 2011/2012,, Report from International Cocoa Organization (ICCO)., ().   Google Scholar

[2]

L. Bengtsson, X. Lu, A. Thorson, R. Garfield and J. von Schreeb, Improved response to disasters and outbreaks by tracking population movements with mobile phone network data: A post-earthquake geospatial study in Haiti,, PLoS Medicine, 8 (2011).   Google Scholar

[3]

V. D. Blondel et al., Data for development: The D4D challenge on mobile phone data,, , (2012).   Google Scholar

[4]

V. D. Blondel, J.-L. Guillaume, R. Lambiotte and E. Lefebvre, Fast unfolding of communities in large networks,, J. Stat. Mech., 10 (2008).   Google Scholar

[5]

S. Bocaletti, V. Latora, Y. Moreno, M. Chavez and D.-U. Hwang, Complex networks: Structure and dynamics,, Phys. Rep., 424 (2006), 175.  doi: 10.1016/j.physrep.2005.10.009.  Google Scholar

[6]

J. Bollen, H. Mao and X.-J. Zeng, Twitter mood predicts the stock market,, J. Comput. Science, 2 (2011), 1.  doi: 10.1016/j.jocs.2010.12.007.  Google Scholar

[7]

, Cote d'Ivoire Roads Shapefiles, Service from African Development Bank., Available from: , ().   Google Scholar

[8]

Document de strategie pays et programe indicatif national pour la periode 2008-2013, Report from Communaute europeenne - Republique de Côte d'Ivoire, 2008., Available from: , ().   Google Scholar

[9]

N. Eagle, M. Macy and R. Claxton, Network diversity and economic development,, Science, 328 (2010), 1029.  doi: 10.1126/science.1186605.  Google Scholar

[10]

T. Hastie, et al., The Elements of Statistical Learning,, Springer, (2009).  doi: 10.1007/978-0-387-84858-7.  Google Scholar

[11]

D. Lazer, et al., Life in the network: The coming age of computational social science,, Science, 323 (2009), 721.   Google Scholar

[12]

M. P. Lewis, Ethnologue: Languages of the World,, $16^{th}$ edition, (2009).   Google Scholar

[13]

M. Lim, R. Metzler and Y. Bar-Yam, Global pattern formation and ethnic/cultural violence,, Science, 317 (2007), 1540.  doi: 10.1126/science.1142734.  Google Scholar

[14]

A. J. Morales, J. Borondo, J. C. Losada and R. M. Benito, Efficiency of human activity on information spreading on Twitter,, Social Networks, 39 (2014), 1.  doi: 10.1016/j.socnet.2014.03.007.  Google Scholar

[15]

M. E. J. Newman, Modularity and community structure in networks,, Phys. Rev. E, 103 (2006), 8577.  doi: 10.1073/pnas.0601602103.  Google Scholar

[16]

M. E. J. Newman, Mixing patterns in networks,, Physical Review E, 67 (2003).  doi: 10.1103/PhysRevE.67.026126.  Google Scholar

[17]

D. Pastor, A. J. Morales, Y. Torres, J. Bauer, A. Wadhwa, C. Castro-Correa, A. Calderón-Mariscal, L. Romanoff, J. Lee, A. Rutherford, V. Frias-Martinez, N. Oliver, E. Frias-Martinez and M. Luengo-Oroz, Flooding through the lens of mobile phone activity,, in IEEE Global Humanitarian Technology Conference (GHTC), (2014), 279.  doi: 10.1109/GHTC.2014.6970293.  Google Scholar

[18]

A. Pentland, Social Physics: How Good Ideas Spread. The Lessons From a New Science,, Penguin Group (USA) Incorporated, (2014).   Google Scholar

[19]

K. K. Rachuri, M. Musolesi, C. Mascolo, P. J. Rentfrow, C. Longworth and A. Aucinas, EmotionSense: A mobile phones based adaptive platform for experimental social psychology research,, Proceedings of the 12th ACM International Conference on Ubiquitous Computing (New York, (2010), 281.  doi: 10.1145/1864349.1864393.  Google Scholar

[20]

T. Sakaki, M. Okazaki and Y. Matsuo, Earthquake shakes twitter users: Real-time event detection by social sensors,, Proceedings of the 19th International Conference on World Wide Web (New York, (2010), 851.  doi: 10.1145/1772690.1772777.  Google Scholar

[21]

J. L. Toole, M. Ulm, M. C González and D. Bauer, Inferring land use from mobile phone activity,, in Proceedings of the ACM SIGKDD International Workshop on Urban Computing, (2012), 1.  doi: 10.1145/2346496.2346498.  Google Scholar

[22]

A. Wesolowski, et al., Quantifying the impact of human mobility on malaria,, Science, 338 (2012), 267.   Google Scholar

[23]

, =, ().   Google Scholar

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