most cited"Don't quote me on that": Finding Mixtures of Sources in News Articles

8 citations · 13 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL20218 cited

"Don't quote me on that": Finding Mixtures of Sources in News Articles

Alexander Spangher, Nanyun Peng, Jonathan May +1

Journalists publish statements provided by people, or \textit{sources} to contextualize current events, help voters make informed decisions, and hold powerful individuals accountab…

cs.CL20211 cited

Modeling "Newsworthiness" for Lead-Generation Across Corpora

Alexander Spangher, Nanyun Peng, Jonathan May +1

Journalists obtain "leads", or story ideas, by reading large corpora of government records: court cases, proposed bills, etc. However, only a small percentage of such records are i…

cs.CL20214 cited

Multitask Learning for Class-Imbalanced Discourse Classification

Alexander Spangher, Jonathan May, Sz-rung Shiang +1

Small class-imbalanced datasets, common in many high-level semantic tasks like discourse analysis, present a particular challenge to current deep-learning architectures. In this wo…

cs.SI2018

Analysis of Strategy and Spread of Russia-sponsored Content in the US in 2017

Alexander Spangher, Gireeja Ranade, Besmira Nushi +2

The Russia-based Internet Research Agency (IRA) carried out a broad information campaign in the U.S. before and after the 2016 presidential election. The organization created an ex…

stat.ML2018

Actionable Recourse in Linear Classification

Berk Ustun, Alexander Spangher, Yang Liu

Machine learning models are increasingly used to automate decisions that affect humans - deciding who should receive a loan, a job interview, or a social service. In such applicati…