Humans are involved in various real-life networked systems. The most obvious examples
are social and collaboration networks but the language and the related mental lexicon
they use, or the physical map of their territory can also be interpreted as networks.
How do they find paths between endpoints in these networks? How do they obtain information
about a foreign networked world they find themselves in, how they build mental model
for it and how well they succeed in using it? Large, open datasets allowing the exploration
of such questions are hard to find. Here we report a dataset collected by a smartphone
application, in which players navigate between fixed length source and destination
English words step-by-step by changing only one letter at a time. The paths reflect
how the players master their navigation skills in such a foreign networked world.
The dataset can be used in the study of human mental models for the world around us,
or in a broader scope to investigate the navigation strategies in complex networked
systems.
