  Narrative sensemaking is a fundamental process to understand sequential
information. Narrative maps are a visual representation framework that can aid
analysts in this process. They allow analysts to understand the big picture of
a narrative, uncover new relationships between events, and model connections
between storylines. As a sensemaking tool, narrative maps have applications in
intelligence analysis, misinformation modeling, and computational journalism.
In this work, we seek to understand how analysts construct narrative maps in
order to improve narrative map representation and extraction methods. We
perform an experiment with a data set of news articles. Our main contribution
is an analysis of how analysts construct narrative maps. The insights extracted
from our study can be used to design narrative map visualizations, extraction
algorithms, and visual analytics tools to support the sensemaking process.
