More of the social world lives within electronic text than ever before, from collective activity
on the web, social media, and instant messaging to online transactions, government …

Parliamentary and legislative debate transcripts provide access to information concerning
the opinions, positions, and policy preferences of elected politicians. They attract attention …

In 2015, Reddit closed several subreddits-foremost among them r/fatpeoplehate and
r/CoonTown-due to violations of Reddit's anti-harassment policy. However, the effectiveness …

We explore the task of predicting the leading political ideology or bias of news articles. First,
we collect and release a large dataset of 34,737 articles that were manually annotated for …

Texts like news, encyclopedias, and some social media strive for objectivity. Yet bias in the
form of inappropriate subjectivity—introducing attitudes via framing, presupposing truth, and …

Word embeddings, the coefficients from neural network models predicting the use of words
in context, have now become inescapable in applications involving natural language …

An individual's words often reveal their political ideology. Existing automated techniques to
identify ideology from text focus on bags of words or wordlists, ignoring syntax. Taking …

The Media Frames Corpus: Annotations of Frames Across Issues Page 1 Proceedings of the
53rd Annual Meeting of the Association for Computational Linguistics and the 7th International …

We consider the problem of automatically inferring latent character types in a collection of
15,099 English novels published between 1700 and 1899. Unlike prior work in which …

Estimating the political leanings of social media users is a challenging and ever more
pressing problem given the increase in social media consumption. We introduce Retweet …