Historical growth of concept networks in Wikipedia

Abstract

Philosophers of science have long questioned how collective scientific knowledge grows. Although disparate answers have been posited, empirical validation has been challenging due to limitations in collecting and systematizing large historical records. Here, we introduce new methods to analyze scientific knowledge formulated as a growing network of articles on Wikipedia and their hyperlinks. We demonstrate that in Wikipedia, concept networks in subdisciplines of science do not grow by expanding from their central core to reach an ancillary periphery. Instead, science concept networks in Wikipedia grow by creating and filling knowledge gaps. Notably, the process of gap formation and closure may be valued by the scientific community, as evidenced by the fact that it produces discoveries that are more frequently awarded Nobel prizes than other processes. To determine whether and how the gap process is interrupted by paradigm shifts, we operationalize a paradigm as a particular subdivision of scientific concepts into network modules. Hence, paradigm shifts are reconfigurations of those modules. The approach allows us to identify a temporal signature in structural stability across scientific subjects in Wikipedia. In a network formulation of scientific discovery, our findings suggest that data-driven conditions underlying scientific breakthroughs depend as much on exploring uncharted gaps as on exploiting existing disciplines and support policies that encourage new interdisciplinary research.

Persistent homology centrality improves link prediction performance in Pubmed co-occurrence networks

“…Extending upon the work from CSGNs, it has been observed that the growth of Wikipedia articles can be modeled and predicted using this same TDA framework. 14 The premise of the papers on Wikipedia growth networks closely related to the work presented in this paper; though with key differences in methodology and scope. First, the data used in this paper is from the scientific literature, and not from the aggregated and filtered knowledge base of Wikipedia.…”

Curiosity and networks of possibility

“…Scientific discovery is not recognized in all directions nor are all its practitioners rewarded equally. The above study, for example, shows that scientific discoveries that form or fill gaps in scientific knowledge are more likely to be offered Nobel prizes than discoveries that lay edges in decontextualized directions (Ju et al, 2022). This suggests that discoveries that exploit adjacent possibilities most connected to existing science are preferentially recognized.…”

“…Imre Lakatos softened Kuhn's theory and suggested science proceeds through research programs that are built via refutation and reconstruction. In a recent study of Wikipedia, we analyzed the development of concept networks across scientific history (Ju et al, 2022). We found that conceptual gaps or network cavities are filled on a regular basis, while a rewiring of the network overall happened more slowly, effecting gradual change in the modular network structure.…”

A Simple Model of Knowledge Scaffolding Applied to Wikipedia Growth

“…This happens because the knowledge network of Wikipedia not only grows bigger but it also "expands" inward by filling knowledge holes (gaps). According to the literature, the process of gap formation and filling should be valued by the scientific community, since it produces discoveries that are more often awarded Nobel prizes than other processes [29].…”