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The complexity and diversity of today's media landscape provides manychallenges for researchers studying news producers. These producers use manydifferent strategies to get their message believed by readers through thewriting styles they employ, by repetition across different media sources withor without attribution, as well as other mechanisms that are yet to be studieddeeply. To better facilitate systematic studies in this area, we present alarge political news data set, containing over 136K news articles, from 92 newssources, collected over 7 months of 2017. These news sources are carefullychosen to include well-established and mainstream sources, maliciously fakesources, satire sources, and hyper-partisan political blogs. In addition toeach article we compute 130 content-based and social media engagement featuresdrawn from a wide range of literature on political bias, persuasion, andmisinformation. With the release of the data set, we also provide the sourcecode for feature computation. In this paper, we discuss the first release ofthe data set and demonstrate 4 use cases of the data and features: newscharacterization, engagement characterization, news attribution and contentcopying, and discovering news narratives.

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