chiarap2 / MASTER

MASTER

Multiple ASpect TrajEctoRy management and analysis

---

In order to monitor the tourism flow in Santorini Island, the questions we want to answer are:

a) Which is the origin Country of travelers?

b) How long do the tourists stay in Santorini?

c) Are the first-time visitors and returning visitors behaving differently?

d) Can we predict the tourist arrival flows?

e) Which is the qualitative level of satisfaction / dissatisfaction of the user?

The project is organized as follow:

MASTER/
│
├── datasets/
│   ├── airbnb/
│   ├── flights/
│   ├── tweets/
│   └── osm/
│
└── research_questions/
    │
    ├── RQ_A_which_is_the_origin_country_of_travelers/
    │   ├── outputs/
    │   └── code.ipynb
    │
    ├── RQ_B_how_long_do_tourist_stay/
    │   ├── outputs/
    │   └── code.ipynb
    │
    ├── RQ_C_are_the_first_visitors_and_returning_visitors_behaving_differently/
    │   ├── outputs/
    │   └── code.ipynb
    │
    ├── RQ_D_predict_arrival_departure_flow/
    │   ├── outputs/
    │   └── code.ipynb
    │
    └── RQ_E_which_is_the_qualitative_level_of_satisfaction_dissatisfaction_of_users/
        ├── outputs/
        └── code.ipynb

In the dataset folder there is one subfolder for each dataset needed for the analysis.

In the twitter folder, you can directly insert files from the Twitter streaming API.

In the airbnb folder, you can insert a airbnb.csv file with at least the following columns:

• id: the room/flat identifier;
• name: the room/flat name;
• neighbourhood: the location name;
• latitute: the room/flat latitude;
• longitude: the room/flat longitude;
• mimimum_nights: the minimum number of nights required to book.

In the osm folder, you can insert the santorini.gpx file containing the trajectories from OpenStreetMap API (you can download it from JOSM application - https://josm.openstreetmap.de/, selecting the bounding box of Santorini).

In the flights folder, you can insert files containing the information about the number of domestic and international passengers per month and year.

In the research_questions folder, you can find a folder for each of the five questions described above. In each of these folders, you find a file with the .ipynb extension in which we analyse the datasets described above and an output subfolder with the results (represented with both plots and description files).

Installation

If you want to run code locally, you can download the entire repository and install the requirements as follow:

pip install -r requirements.txt