Danube Delta is the second largest European delta, a UNESCO World Heritage Site, and a famous paradise for nature lovers and bird watchers, which attracts increasing numbers of tourists every year. The article uses mixed methods, qualitative (i.e., narratives) and quantitative (i.e., computer) analyses, to examine the main components of visitors' subjective experiences of the Danube Delta. Data is represented by online visitor reviews, posted between 2011 and 2017 on the TripAdvisor website. The results showed that experiences of the Danube Delta are mostly positive and centered on direct contact with nature and wildlife. However, managerial aspects linked to visit organization, such as boat types, trip itinerary, duration, or food, were more prominent in the tourists’ impressions and recommendations, compared to destination attributes. Experiences of the Danube Delta are mostly passive, dominantly visual, with low visitor emotional and physical engagement. The cultural and environmental dimensions are underrepresented in people's reviews.

The study of visitor experiences incorporating user-generated content from accommodation platforms is a distinct trend in the geography of tourism. Our research aims to better understand how this content can be instrumentalized in order to assess the viability of Airbnb accommodation ranks based on specific case studies from Greece, Italy, and Spain. The methodological frame we propose is based on two separate tools. First, the users’ reviews are summarized using sentiment analysis techniques, and the positive component is extracted as a separate indicator (predictor). The second step consists of mobilizing geographically weighted regression (GWR) to identify of the potential statistical association between the Airbnb apartments’ ranks and the quantitative outputs of sentiment analysis. The results obtained for 13 case studies are based on more than 4.6 million reviews. They clearly emphasize a gap between the rank proposed by the platform and the positive scores of sentiment analysis for the accommodation units analyzed (88,053). Despite some limitations linked to the quantity of data needed to be integrated into the investigation, the methodological frame can be transferred to other destinations, providing useful information about the potential distortions of tourism markets by the meta-description of accommodation systems.

The territorial contexts in which the universities are supposed to function become more and more complex and involve different forms of military, social and political risks. This article examines potential methodological approaches for evaluating these risks, using the network of AUF universities as a case study. The data used for the evaluation are provided by the ACLED datasets of incidents at a world scale, and they were spatialized using classical GIS tools. The first methodological approach measures the university's exposure by placing them in different distance bands around the median centers of significant state and non-state actors responsible for the military conflicts between 2021 and 2025. The output of the second approach is a multivariate typology of the AUF universities, each class describing different forms of exposure to risks. The key findings underline the fact that there are substantial disparities between the AUF regions, in terms of exposure, with severe risks in Western Africa, the Middle East and Eastern Europe.0 Based on the results of the research, a set of recommendations for policy design inside AUF was developed.

This study evaluates the impact of different territorial contexts on academic mobility within the framework of the Erasmus Programme, using data on Key Action 1 exchanges between 2015 and 2023. Using official EU datasets and a gravity model framework, the research investigates how economic performance, geographical distance, EU membership, AUF (Agence Universitaire de la Francophonie) regional affiliation, and state contiguity shape international academic flows. The research developed two gravity models: one aimed to measure the potential barriers to academic flows through a residuals analysis, and the second integrated territorial delineations as predictors. In both models, the core of the explanatory variable is formed by indicators describing the economic performance of states and the distance between countries. When applied, the models converge in emphasizing that the inclusion of states in different territorial configurations has a strong effect on the structuring of academic flows. This suggests that the Erasmus Programme exhibits trends of overconcentration of flows in a limited number of countries, questioning the need for a more polycentric strategy and a reshaping of the funding mechanisms. Even if the gravity models behave well, given the limited number of predictors, further studies may need to incorporate qualitative indicators for a more comprehensive evaluation of the interactions.