author

Romeo De Timmerman

project summary

This repository contains a quantitative analysis of Flemish contact tracing data from July 15, 2020 through December 10, 2020. This analysis is part of the larger Contra-C19 research project titled 'Effective information exchange and care orientation in Covid-19-related contact tracing phone calls. An applied sociolinguistic and conversation analytic enquiry into optimizing interactional dynamics and pragmatic awareness.' This project was funded by the Flemish Research Council (FWO), and was carried out by researchers from Ghent University and the University of Antwerp.

project structure

`` ├── LICENSE ├── README.md <- The top-level README for developers using this project. ├── data │ ├── interim <- Intermediate data that has been transformed. │ ├── processed <- The final, canonical data sets for modeling. │ └── raw <- The original, immutable data dump. │ ├── docs <- Documents │ ├── models <- Trained and serialized models, model predictions, or model summaries │ ├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering), │ the creator's initials, and a short-delimited description, e.g. │1.0-rdt-initial-data-exploration. │ ├── figures <- Generated graphics and figures to be used in reporting │ ├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g. │ generated withpip freeze > requirements.txt` │ ├── src <- Source code for use in this project. │ ├── init.py <- Makes src a Python module │ │ │ ├── data <- Scripts to download or generate data │ │ └── makedataset.py │ │ │ ├── features <- Scripts to turn raw data into features for modeling │ │ └── buildfeatures.py │ │ │ ├── models <- Scripts to train models and then use trained models to make │ │ │ predictions │ │ ├── predictmodel.py │ │ └── trainmodel.py │ │ │ └── visualization <- Scripts to create exploratory and results oriented visualizations └── visualize.py

(this project structure is based on the Cookiecutter Data Science template) ```