The immense growth of the social Web, which has made a large amount of user
data easily and publicly available, has opened a whole new spectrum for
research in social behavioral sciences. However, as the volume of social media
content increases at a very fast rate, it becomes extremely difficult to
systematically obtain high-level information from this data. As a consequence,
tasks related to the analysis of historical news events based on social media
data have not been explored, which limits any type of comparative historical
research, causality analysis, and discovery of knowledge from patterns
extracted from aggregated social media event information.