# Learning Patterns of Tourist Movement and Photography from Geotagged Photos at Archaeological Heritage Sites in Cuzco, Peru

arXiv: https://arxiv.org/abs/2006.16424 · HTML: https://mlsanity.com/paper/2006.16424/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Jun 2020.

## Built on by (most cited first, 2 of 2)

- [Text2Traj2Text: Learning-by-Synthesis Framework for Contextual Captioning of Human Movement Trajectories](https://mlsanity.com/paper/2409.12670/) (2024)
- [Identifying tourist destinations from movie scenes using Deep Learning](https://mlsanity.com/paper/2312.00098/) (2023)

## Abstract (arXiv)

The popularity of media sharing platforms in recent decades has provided an abundance of open source data that remains underutilized by heritage scholars. By pairing geotagged internet photographs with machine learning and computer vision algorithms, we build upon the current theoretical discourse of anthropology associated with visuality and heritage tourism to identify travel patterns across a known archaeological heritage circuit, and quantify visual culture and experiences in Cuzco, Peru. Leveraging large-scale in-the-wild tourist photos, our goals are to (1) understand how the intensification of tourism intersects with heritage regulations and social media, aiding in the articulation of travel patterns across Cuzco's heritage landscape; and to (2) assess how aesthetic preferences and visuality become entangled with the rapidly evolving expectations of tourists, whose travel narratives are curated on social media and grounded in historic site representations.