TY - GEN
T1 - From Flows to Graphs
T2 - Short papers, Doctoral Consortium and workshop papers which were presented at the 29th European Conference on New Trends in Databases and Information Systems, ADBIS 2025
AU - Alatrista-Salas, Hugo
AU - Chareyron, Gaël
AU - Djebali, Sonia
AU - Ouled-Dlala, Imen
AU - Travers, Nicolas
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
PY - 2026
Y1 - 2026
N2 - Overtourism presents complex and often hidden challenges for urban environments, impacting residents, infrastructure, and visitor satisfaction. This study proposes a novel, data-driven methodology to detect and analyze latent overtourism—the early, subtle warning signs of excessive tourism—before visible breakdowns occur. By leveraging user-generated content from Tripadvisor, a temporal circulation multidigraph is modeled to capture tourist mobility. Using frequent subgraph mining algorithms, the approach identifies recurring tourist movement patterns across different urban scales. These patterns are then analyzed in both spatial and temporal dimensions to detect hotspots and evaluate dynamic attractiveness through a Huff-based probabilistic model. The approach is applied to three cities of varying sizes revealing consistent tourist flows and areas under increasing pressure, suggesting early overtourism.
AB - Overtourism presents complex and often hidden challenges for urban environments, impacting residents, infrastructure, and visitor satisfaction. This study proposes a novel, data-driven methodology to detect and analyze latent overtourism—the early, subtle warning signs of excessive tourism—before visible breakdowns occur. By leveraging user-generated content from Tripadvisor, a temporal circulation multidigraph is modeled to capture tourist mobility. Using frequent subgraph mining algorithms, the approach identifies recurring tourist movement patterns across different urban scales. These patterns are then analyzed in both spatial and temporal dimensions to detect hotspots and evaluate dynamic attractiveness through a Huff-based probabilistic model. The approach is applied to three cities of varying sizes revealing consistent tourist flows and areas under increasing pressure, suggesting early overtourism.
KW - Frequent Pattern Mining
KW - Graph mining
KW - Overtourism
KW - Social Media
UR - https://www.scopus.com/pages/publications/105017374169
U2 - 10.1007/978-3-032-05727-3_28
DO - 10.1007/978-3-032-05727-3_28
M3 - Conference contribution
AN - SCOPUS:105017374169
SN - 9783032057266
T3 - Communications in Computer and Information Science
SP - 327
EP - 342
BT - New Trends in Database and Information Systems - ADBIS 2025 Short Papers, Workshops, Doctoral Consortium and Tutorials, 2025, Proceedings
A2 - Chrysanthis, Panos K.
A2 - Nørvåg, Kjetil
A2 - Stefanidis, Kostas
A2 - Zhang, Zheying
A2 - Quintarelli, Elisa
A2 - Zumpano, Ester
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 23 September 2025 through 26 September 2025
ER -