Big Data, Mobility and Rhythms in Istanbul: A Data-Driven Analysis of Urban Temporal Dynamics

This study explores the spatio-temporal dynamics of Istanbul’s urban mobility by applying a four-stage urban rhythm analysis framework that combines big data analytics with urban theory. Using Istanbul Card data, it reveals how urban rhythms are shaped by social calendars, institutional schedules, and daily practices across different temporal scales (year, season, month, week, day). The findings highlight polyrhythmic nodes—such as the Metrobus corridor and Zincirlikuyu hub—where commuting, leisure, and touristic flows converge, and identify arrhythmias during national holidays and religious festivals. By integrating Lefebvre’s rhythmanalysis and Bakhtin’s chronotope, the study demonstrates how big data can move beyond descriptive analytics to reveal the layered temporalities of urban life. Additionally, the research addresses the Modifiable Temporal Unit Problem (MTUP) by developing a multiscalar methodology that minimizes temporal distortion and enhances the interpretability of rhythm patterns. The results provide actionable insights for adaptive urban planning and transport management, demonstrating how rhythm-based big data analytics can uncover hidden dynamics of urban character and guide more resilient, inclusive mobility strategies.