Abstract
Understanding the variability in citizens' travel behavior within a city is essential for comprehending urban mobility. However, obtaining daily data on these journeys through traditional methods is expensive. Although alternative methods, such as using social media data, are widely employed in the academic community, they have contributed little due to the low representativeness of the data and the lack of efforts to understand user behavior. This study fills this gap by analyzing travel variability in Fortaleza using social media data from platforms like Instagram and Twitter. Employing empirical and parametric statistical techniques, such as box plots and statistical tests (ANOVA, Kruskal-Wallis, and Tukey), hypotheses based on a literature review analysis were validated. The results revealed patterns similar to those observed in daily life and also yielded unexpected conclusions about the phenomenon. Despite limitations regarding data representativeness, important insights were obtained for understanding daily travel patterns in Fortaleza.
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