  Network science and data analytics are used to quantify static and dynamic
structures in George R.R. Martin's epic novels, A Song of Ice and Fire, works
noted for their scale and complexity. By tracking the network of character
interactions as the story unfolds, it is found that structural properties
remain approximately stable and comparable to real-world social networks.
Furthermore, the degrees of the most connected characters reflect a cognitive
limit on the number of concurrent social connections that humans tend to
maintain. We also analyse the distribution of time intervals between
significant deaths measured with respect to the in-story timeline. These are
consistent with power-law distributions commonly found in inter-event times for
a range of non-violent human activities in the real world. We propose that
structural features in the narrative that are reflected in our actual social
world help readers to follow and to relate to the story, despite its sprawling
extent. It is also found that the distribution of intervals between significant
deaths in chapters is different to that for the in-story timeline; it is
geometric rather than power law. Geometric distributions are memoryless in that
the time since the last death does not inform as to the time to the next. This
provides measurable support for the widely held view that significant deaths in
A Song of Ice and Fire are unpredictable chapter-by-chapter.
