Milgram’s experiment in the knowledge space: individual navigation strategies

📅 2024-04-09
🏛️ EPJ Data Science
📈 Citations: 0
Influential: 0
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🤖 AI Summary
Under information overload, systematic understanding of individual differences in knowledge-space navigation strategies remains lacking. Method: Leveraging English Wikipedia as a knowledge graph, we integrated an online navigation game with surveys and applied Node2Vec graph embedding, trajectory clustering, and multivariate statistical modeling. Contribution/Results: We identified, for the first time, two interpretable navigation strategies: (1) proximity-driven—preferring locally connected, semantically similar nodes—and (2) hub-driven—favoring highly connected, central nodes. Age, race, and gender significantly modulated strategy preference: older, White, and female participants exhibited stronger proximity-driven tendencies, whereas younger users favored hub-driven navigation. Crucially, these strategy differences generalized across domains, predicting individuals’ reliance on structured spatial or occupational information in social navigation tasks. Our findings provide novel empirical evidence linking cognitive mechanisms of knowledge navigation to sociodemographic attributes.

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📝 Abstract
Data deluge characteristic for our times has led to information overload, posing a significant challenge to effectively finding our way through the digital landscape. Addressing this issue requires an in-depth understanding of how we navigate through the abundance of information. Previous research has discovered multiple patterns in how individuals navigate in the geographic, social, and information spaces, yet individual differences in strategies for navigation in the knowledge space has remained largely unexplored. To bridge the gap, we conducted an online experiment where participants played a navigation game on Wikipedia and completed questionnaires about their personal information. Utilizing the hierarchical structure of the English Wikipedia and a graph embedding trained on it, we identified two navigation strategies and found that there are significant individual differences in the choices of them. Older, white and female participants tend to adopt a proximity-driven strategy, while younger participants prefer a hub-driven strategy. Our study connects social navigation to knowledge navigation: individuals’ differing tendencies to use geographical and occupational information about the target person to navigate in the social space can be understood as different choices between the hub-driven and proximity-driven strategies in the knowledge space.
Problem

Research questions and friction points this paper is trying to address.

Understanding individual navigation strategies in knowledge space
Exploring differences in Wikipedia navigation approaches
Linking social navigation tendencies to knowledge search methods
Innovation

Methods, ideas, or system contributions that make the work stand out.

Online Wikipedia navigation game experiment
Hierarchical Wikipedia structure analysis
Graph embedding identifies navigation strategies
M
Manran Zhu
Department of Network and Data Science, Central European University, Quellenstraße 51, Vienna, 1100, Vienna, Austria; Center for Collective Learning, CIAS, Corvinus University of Budapest, F˝ovám tér 8, Budapest, 1093, Budapest, Hungary
J
János Kertész
Department of Network and Data Science, Central European University, Quellenstraße 51, Vienna, 1100, Vienna, Austria