Understanding news story chains using information retrieval and network clustering techniques

Content analysis of news stories (whether manual or automatic) is a cornerstone of the communication studies field. However, much research is conducted at the level of individual news articles, despite the fact that news events (especially significant ones) are frequently presented as “stories” by news outlets: chains of connected articles covering the same event from different angles. These stories are theoretically highly important in terms of increasing public recall of news items and enhancing the agenda-setting power of the press. Yet thus far, the field has lacked an efficient method for detecting groups of articles which form stories in a way that enables their