Data transformation Using a New York Times API in R

Author

Pascal Hermann Kouogang Tafo

INTRODUCTION

This assignment consists of using the New York Times Article Search API to examine how the volume and framing of soccer coverage in the New York Times has evolved since the modern Major League Soccer (MLS) expansion era began in 2005.In fact d,API provides rich article-level metadata such as headline, publication date, section name, news desk, word count, and multimedia flags since 1851, making it well suited for detecting decade-long window in editorial attention and story framing by querying the keyword “soccer”.

APPROACH

Below is a structured workflow approach to accomplish our goal and answer our question:

  1. Use a securely stored environment variable to Access the NYT Article Search and prevent API key exposure

  2. Filter and Collect the most recent articles containing the keyword “soccer” at request time to ensure a contemporary dataset. The result will contain several fields as nested lists such as “headline”, “keywords”, “byline`”, “multimedia” etc…

  3. Then i will parse each paginated JSON response into a data frame specifically by extracting only the sub-fields i need and collapsing arrays to scalar values.

  4. Finally, clean the data to calculate which newspaper sections are producing the most content on “SOCCER”.