High-Resolution Maps of Science from Clickstream Data
Author Information
Author(s): Bollen Johan, Van de Sompel Herbert, Hagberg Aric, Bettencourt Luis, Chute Ryan, Rodriguez Marko A., Balakireva Lyudmila
Primary Institution: Los Alamos National Laboratory
Hypothesis
Can valid, high-resolution maps of science be derived from clickstream data?
Conclusion
Maps of science resulting from large-scale clickstream data provide a detailed, contemporary view of scientific activity and correct the underrepresentation of the social sciences and humanities that is commonly found in citation data.
Supporting Evidence
- The study analyzed nearly 1 billion user interactions to create a comprehensive map of scientific activity.
- The resulting maps correct the underrepresentation of social sciences and humanities in traditional citation data.
- The methodology allows for real-time tracking of scholarly behavior.
Takeaway
This study shows how we can use data from people clicking on articles online to create detailed maps of science, helping us see how different fields are connected.
Methodology
The study collected nearly 1 billion user interactions from scholarly web portals and analyzed them to create a clickstream model of journal relationships.
Potential Biases
The data may be influenced by the specific web portals used and their user interfaces.
Limitations
The study's findings are based on aggregated log data, which may not capture all nuances of scholarly behavior.
Participant Demographics
The data reflects a broad community of users, including scientific authors, practitioners, and the informed public.
Digital Object Identifier (DOI)
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