• stigmergy
• optimization
• Istanbul
• hotspots
• differential evolution
• transactions

Mobility payments are increasing nowadays. With the increase in transactions, the amount of data to be maintained and processed has also increased. In today’s historical period, it is extremely important to ex tract knowledge and useful information from bank transaction logs. Knowing ”How money moves” within a large city can provide support to economists and sociologists to outline implicit mobil ity behaviors and welfare of the population and create statistics describing precarious financial conditions. This thesis proposed a novel approach to tackle data mining in the field of city science and identify permanent hotspots, areas of the city that are relevant in terms of transactions. The stigmergic paradigm proved to be an excellent fit for city-scale mobility data, easing designers from the burden of creating complex mathematical and statistical models to infer knowledge from such data.