This repository contains a Jupyter Notebook which generates visualisations based on mobile browser history.
Online and mobile news consumption leaves digital traces that are used to personalize news supply, possibly creating filter bubbles where people are exposed to a low diversity of issues and perspectives that match their preferences. The JEDS Filter Bubble project aims to understand the filter bubble effect by performing deep semantic analyses on mobile news consumption traces. This project is a collaboration between the VU, the UvA and NLeSC, lead by Wouter van Atteveldt.
Part of this project includes gathering data from a group of participants. These fill in a questionnaire and consent to giving us their browsing history. The Jupyter Notebook in this repository provides some preliminary descriptive statistics on our data.
The data directory contains the Qualtrics survey data and the Passive Data Kit and Web Historian browsing history. Due to the privacy sensitivity of the data, the entire directory is gitignored.
The figures directory contains saved output of the Jupyter Notebook which visualise aggregate statistics of our data.
The tables directory contains saved output of the Jupyter Notebook which list aggregate statistics of our data.
This Jupyter Notebook imports the data, cleans and restructures it and subsequently outputs various aggregate descriptive statistics.