Unveiling connectivity patterns of categories in complex systems: An application to human needs in urban places

ABSTRACT

We present a methodology based on weighted networks and dependence coefficients aimed at revealing connectivity patterns between categories. As a case study, it is applied to an urban place and at two spatial levels—neighborhood and square—where categories correspond to human needs. Our results show that diverse spatial levels present different and nontrivial patterns of need emergence. A numerical model indicates that these patterns depend on the probability distribution of weights. We suggest that this way of analyzing the connectivity of categories (human needs in our case study) in social and ecological systems can be used to define new strategies to cope with complex processes, such as those related to transition management and governance, urban-making, and integrated planning.

KEYWORDS:

• Complex networks
• human-scale development
• maximal information coefficient
• qualitative and quantitative analysis
• urban places

Acknowledgements

The authors would like to thank one anonymous reviewer for her comments and deep insight, which have clearly improved the quality and the final overall form and contents of the paper. One author (IP) thanks specially Ch. Eppes for illuminating conversations on social networks and modelling.

Notes

¹ http://www.share-project.org/

² http://www.worldvaluessurvey.org/

³ http://www.grossnationalhappiness.com/

⁴ http://lameva.barcelona.cat/gracia/ca/home/el-barri-de-la-vila-de-gracia

⁵ http://graciapedia.gracianet.cat

⁶ Survey questions can be found in the Appendix.

⁷ http://summlab.upc.edu/en

⁸ https://is.upc.edu/?set_language=en

⁹ MIC code can be downloaded from http://www.exploredata.net. The page also offers real data examples, the necessary steps to compute MIC value and an explanation regarding its parameters.