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The paper aims to present a literary itinerary inspired in Julio Dinis’ novel An English Family (Uma Família Inglesa) through a comparative analysis of the places identified in the novel and the touristic attraction proposed by Visit Porto website. This novel is representative of the cultural identity and society of Porto city in the 19th century. Developing an itinerary based on this novel can facilitate the reading and understanding of the historical and cultural development of Porto.

This case study is based on the reading of the Julio Dinis’ novel An English Family (Uma Família Inglesa), whose storyline takes place in Porto city, Portugal in the 19th century. It used QGIS v. 3.12 software, a geographical information system to identify the places, to produce the maps and to create the itinerary.

The comparison between the places identified in the novel and the tourist attraction in Visit Porto website revealed that only 6 points in the novel are referenced on Visit Porto website. These points correspond to the ones in the historical city centre of Porto. However, the creation of an itinerary that brings together all the points mentioned by Julio Dinis in his novel, will allow the development of a new touristic itinerary, alternative to existing itineraries in the city and that can be seen as a distinguish offer that allows a different view of the urban space of Porto.

There are some limitations to this study that can be highlighted. First, it was difficult to find the correct location of some points identified in the novel, due to difficulty of finding historical maps with quality of the data. At the same time, as tourist information is dispersed by several sources, and most of those data is not georeferenced, it was time consuming the integration of all the information in the same geodatabase. The choice of the shortest path can also be considered as a limitation, rather than the route followed by the author in the novel, but geographic information systems operates on spatial and temporal scale, which can present a limitation in tourism analysis. In the case of this project, we have chosen the shortest path, assuming that tourist would prefer that.

This research allowed to address two areas of knowledge that are emerging in the study of urban centres as tourist areas: the use of GIS and literary tourism. Despite the fact that there are already articles on this subject, the originality focuses on the approach made around one of the greatest writers of Portugal in the 19th century, allowing to present a tourist itinerary about one of his literary works, and the comparison made between the places identified in the novel and the tourist points identified on the Visit Porto website.

The purpose of this study is to investigate and understand the performance of countries in individual Olympic Games, specifically focusing on the Tokyo 2020 Olympics. Employing cluster analysis and decision trees, the research aims to categorize countries based on their representation, participation and success.

This research employs a data-driven approach to comprehensively analyze and enhance understanding of countries' performances in individual Olympic Games. The methodology involves a two-stage clustering method and decision tree analysis to categorize countries and identify influential factors shaping their Olympic profiles.

The study, analyzing countries' performances in the Tokyo 2020 Olympics through cluster analysis and decision trees, identified five clusters with consistent profiles. Notably, China, Great Britain, Japan, Russian Olympic Committee and the United States formed a high-performing group, showcasing superior success, representation and participation. The analysis revealed a correlation between higher representation/participation and success in individual Olympic Games. Decision tree insights underscored the significance of population size, GDP per Capita and HALE index, indicating that countries with larger populations, better economic standing and higher health indices tended to perform better.

The study has several limitations that should be considered. Firstly, the findings are based on data exclusively from the Tokyo 2020 Olympics, which may limit the generalizability of the results to other editions.

The research offers practical implications for policymakers, governments and sports organizations seeking to enhance their country's performance in individual Olympic Games.

The research holds significant social implications by contributing insights that extend beyond the realm of sports.

The originality and value of this research lie in its holistic approach to analyzing countries' performances in individual Olympic Games, particularly using a two-stage clustering method and decision tree analysis.