Sampling the News Producers: A Large News and Feature Data Set for the Study of the Complex Media Landscape

The complexity and diversity of today's media landscape provides many\nchallenges for researchers studying news producers. These producers use many\ndifferent strategies to get their message believed by readers through the\nwriting styles they employ, by repetition across different media sources with\nor without attribution, as well as other mechanisms that are yet to be studied\ndeeply. To better facilitate systematic studies in this area, we present a\nlarge political news data set, containing over 136K news articles, from 92 news\nsources, collected over 7 months of 2017. These news sources are carefully\nchosen to include well-established and mainstream sources, maliciously fake\nsources, satire sources, and hyper-partisan political blogs. In addition to\neach article we compute 130 content-based and social media engagement features\ndrawn from a wide range of literature on political bias, persuasion, and\nmisinformation. With the release of the data set, we also provide the source\ncode for feature computation. In this paper, we discuss the first release of\nthe data set and demonstrate 4 use cases of the data and features: news\ncharacterization, engagement characterization, news attribution and content\ncopying, and discovering news narratives.\n