Evaluation of Automatic Text Summarization using Synthetic Facts

Authorship
Jay Ahn and Foaad Khosmood
Publication
arXiv
Non refereed paper

Tags

Abstract

In US State government legislatures, most of the activity occurs in committees made up of lawmakers discussing bills. When analyzing, classifying or summarizing these committee proceedings, some important features become broadly interesting. In this paper, we engineer four useful features, two applying to lawmakers (engagement and absence), and two to non-lawmakers (stance and affiliation). We propose a system to automatically track the affiliation of organizations in public comments and whether the organizational representative supports or opposes the bill.