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Causal inference is essential in science studies, yet many publications lack methods to substantiate causal claims. Structural causal models, often represented graphically with directed acyclic graphs, make causal assumptions transparent and improve communication. We illustrate the application with a hypothetical model of Open Science.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |