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A methodology for identifying breakthrough topics using structural entropy
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DOI：10.1016/j.ipm.2021.102862.png)
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This research uses link prediction and structural-entropy methods to predict scientific breakthrough topics. Temporal changes in the structural entropy of a knowledge network can be used to identify potential breakthrough topics. This has been done by tracking and monitoring a network's critical transition points, also known as tipping points. The moment at which a significant change in the structural entropy of a knowledge network occurs may denote the points in time when breakthrough topics emerge. The method was validated by domain experts and was demonstrated to be a feasible tool for identifying scientific breakthroughs early. This method can play a role in identifying scientific breakthroughs and could aid in realizing forward-looking predictions to provide support for policy formulation and direct scientific research.
Keyword:
structural entropy
scientific breakthrough
link prediction
knowledge networks
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6.9
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被引数:
1.4W
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