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README.md

Examining the Comparability of 'Most-Viewed Lists'

Author: Rodrigo Zamith

Description

This repository contains the Python scripts used to download and extract information for the five most viewed items appearing on the homepages of 21 different news organizations at a given time. Additional scripts are offered to help organize the information and produce charts that facilitate an evaluation of the lists of most-viewed items across two dimensions: the rate of change for the list and the median time it takes an item to appear on that list.

These scripts will likely be most useful as a foundation for similar research projects; they will need to be tweaked to adapt them to other websites. If you have any questions, please e-mail me.

The scripts are broken down into three sets:

  • Download scripts: These scripts are used to freeze a liquid homepage into a static snapshot with the browser-processed HTML code and a screenshot of the page at the time the script is run.

  • Parse scripts: These scripts extract information from the aforementioned snapshots. Specifically, the top five items from the list of most-viewed items and all other links appearing on the page (that fit a given URL pattern) are extracted and stored into a database.

  • Dataset scripts: These scripts help to clean and reshape data. Those clean data may then be downloaded from the database, and the R script facilitates an evaluation of the lists of most-viewed items across two dimensions: the rate of change for the list and the median time it takes an item to appear on that list.

Dependencies

These scripts depend on Python, MySQL, and Firefox. Additionally, the Selenium framework and the BeautifulSoup and PyMSQL libraries, and other standard libraries, are used. For the data analysis scripts, R is required.

License

All scripts in this repository are licensed under the Mozilla Public License Version 2.0 (see LICENSE file in the root folder). TL;DR: Feel free to use modify it and distribute it as part of either commercial or non-commercial software, provided you disclose both the source code and any modifications you make to it.