Abstract
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.
Highlights
Background & SummaryThe way people navigate among the world's physical objects is of crucial importance from the perspective of their survival
Some more recent studies have identified similarities between physical and social navigation strategies and hint that people treat the “Where am I?” (i.e. How do I identify myself in the network of physical objects?) question very to the “Who am I?” (i.e. How do I locate myself in the network of social contacts?) question from a navigational point of view[8,9,10,11]
In our modern world it is not necessary to stress that the proper usage of the social network is at least as important as navigating in the physical world from the perspective of survival
Summary
Background & SummaryThe way people navigate among the world's physical objects is of crucial importance from the perspective of their survival. These word chains are collected anonymously, with some other optional metadata about the players (gender, language, year of birth). The word chains in the database can be considered as the footprints of human navigation over the word morph network of the English language and may be good sources for studying human navigation strategies in the future.
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