  We present a study on predicting the factuality of reporting and bias of news
media. While previous work has focused on studying the veracity of claims or
documents, here we are interested in characterizing entire news media. These
are under-studied but arguably important research problems, both in their own
right and as a prior for fact-checking systems. We experiment with a large list
of news websites and with a rich set of features derived from (i) a sample of
articles from the target news medium, (ii) its Wikipedia page, (iii) its
Twitter account, (iv) the structure of its URL, and (v) information about the
Web traffic it attracts. The experimental results show sizable performance
gains over the baselines, and confirm the importance of each feature type.
