  We investigate the overlap of topics of online news articles from a variety
of sources. To do this, we provide a platform for studying the news by
measuring this overlap and scoring news stories according to the degree of
attention in near-real time. This can enable multiple studies, including
identifying topics that receive the most attention from news organizations and
identifying slow news days versus major news days. Our application, StoryGraph,
periodically (10-minute intervals) extracts the first five news articles from
the RSS feeds of 17 US news media organizations across the partisanship
spectrum (left, center, and right). From these articles, StoryGraph extracts
named entities (PEOPLE, LOCATIONS, ORGANIZATIONS, etc.) and then represents
each news article with its set of extracted named entities. Finally, StoryGraph
generates a news similarity graph where the nodes represent news articles, and
an edge between a pair of nodes represents a high degree of similarity between
the nodes (similar news stories). Each news story within the news similarity
graph is assigned an attention score which quantifies the amount of attention
the topics in the news story receive collectively from the news media
organizations. The StoryGraph service has been running since August 2017, and
using this method, we determined that the top news story of 2018 was the
"Kavanaugh hearings" with attention score of 25.85 on September 27, 2018.
Similarly, the top news story for 2019 so far (2019-12-12) is "AG William
Barr's release of his principal conclusions of the Mueller Report," with an
attention score of 22.93 on March 24, 2019.
