  Art Museums traditionally employ observations and surveys to enhance their
knowledge of visitors' behavior and experience. However, these approaches often
produce spatially and temporally limited empirical evidence and measurements.
Only recently has the ubiquity of digital technologies revolutionized the
ability to collect data on human behavior. Consequently, the greater
availability of large-scale datasets based on quantifying visitors' behavior
provides new opportunities to apply computational and comparative analytical
techniques. In this paper, we attempt to analyze visitors' behavior in the
Louvre Museum from anonymized longitudinal datasets collected from noninvasive
Bluetooth sensors. We examine visitors' length of stay in the museum and
consider this relationship with occupation density around artwork. This data
analysis increases the knowledge and understanding of museum professionals
related to the experience of visitors.
