WHEN ALGORITHMS SHAPE TOURIST DESTINATIONS: A SOCIOLOGICAL ANALYSIS OF DIGITAL VISIBILITY, POWER, AND TOURIST DECISION-MAKING IN BALI, INDONESIA
Keywords:
Keywords: Algorithmic visibility, Bali tourism, platform urbanism, sociology of tourism, spatial governance, tourist decision-making, digital nomads, insta- gentrification.Abstract
Algorithms have transitioned from back-end computational procedures to active
socio-technical actors that orchestrate human attention, geographic mobility, and
spatial consumption. This paper provides a sociological analysis of how digital
visibility architectures on major platforms (e.g., Instagram, TikTok, TripAdvisor, and
Little Red Book/Xiaohongshu) reconfigure tourist decision-making, reshape
destination political economies, and restructure island ecosystems. Drawing on a
mixed-methods empirical design combining computational web-scraping of platform
recommendation outputs (N = 16,800 point-of-interest rank profiles across four major
regions in Bali: Canggu, Ubud, Seminyak, and Uluwatu), semi-structured interviews
with local tourism stakeholders and business operators (n = 54), and an online/field
survey of international travelers and digital nomads (n = 1,450), we examine the
operational mechanisms of algorithmic mediation.
Our findings demonstrate that platform curation algorithms generate extreme
'visibility monopolies,' funneling up to 81.6% of tourist foot traffic into narrow spatial
corridors while marginalizing non-digitized or algorithmically incompatible cultural
sites. We show how tourists perform 'algorithmic compliance,' aligning their itinerary
choices and aesthetic behaviors with platform feedback loops to maximize social and
cultural capital. Furthermore, platform mediation exacerbates spatial gentrification,
infrastructure strain, water resource allocation conflicts, and economic inequality
between algorithmically favored enterprises and excluded local actors. We conclude
by offering a theoretical framework of algorithmic spatial governance and discussing
policy interventions to restore democratic spatial planning in digitally mediated
tourism ecosystems.
References
References
1. Baggio, R. (2013). Studying complex tourism systems: a novel approach based on
networks derived from a time series. arXiv preprint arXiv:1302.5909.
2. Gillespie, T. (2010). The politics of 'platforms'. New Media & Society, 12(3), 347–
364. https://doi.org/10.1177/1461444809342738
3. Gross, N., & Mothersill, D. (2023). Surveillance capitalism in mental health: When
good apps go rogue (and what can be done about it). Social Sciences, 12(12), 679.
https://doi.org/10.3390/socsci12120679
4. Gursoy, D., Luongo, S., Della Corte, V., & Sepe, F. (2024). Smart tourism
destinations: an overview of current research trends and a future research agenda.
Journal of Hospitality and Tourism Technology, 15(3), 479–495.
https://doi.org/10.1108/jhtt-10-2023-0339
5. Sun, S., Liu, Z., & Waxman, D. (2023). A dynamical measure of algorithmically
infused visibility. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4648591
6. Zhou, X., Li, R., Teng, F., Pan, J., & Zhao, T. (2024). Tourism recommendation
algorithm based on the mobile intelligent connected vehicle service platform.
Symmetry, 16(11), 1431. https://doi.org/10.3390/sym16111431