Extracting activist events from news articles using existing NLP tools and services

Activists have a significant role in shaping social views and opinions. To find out specifically how they are doing this, social scientists study the events activists are involved in. Unfortunately, individual sources may present incomplete, incorrect, or biased event descriptions. We present a method where we automatically extract event mentions from di↵erent news sources that could complement, contradict, or verify each other. The extraction will ultimately feed a visual analytics application that supports discovery and analysis in large amounts of event data. This document is the full thesis, also attached is a scientific paper that describes the essence of the thesis.