Editorial boycotts and declarations of independence generate a lot of heat, but what do the data say about the actual success of the new journals compared to the journals that were overthrown.
Expert ratings have poorer predictive power than journal citation metrics, study reveals.
Editors have learned how to exploit a simple loophole in the calculation of the Impact Factor. Is it time to close that loophole?
Making sense of non-events (citation, circulation, and publication) requires context and a tolerance for uncertainty.
A new paper demonstrates how easy it is to game Google Scholar citations, and how the system resists correction.
As new metrics are explored, not everything equates to “impact.” Getting our terms right will help us get our thinking straight.
An attempt to entice citations from authors leads to a memorable story for the holidays.
The rankings of journals based on F1000 scores reveals a strong bias against larger journals and those with little disciplinary overlap with the biosciences.
Can tweets predict future citations? A study of article tweets raises validity and ethical concerns.
Rebuttals are cited less, don’t change citation patterns for original papers, and generally fall flat. And you thought science was self-correcting?
Promises of more citations if authors pay are problematic in more ways than one.
A study showing that randomized controlled trials don’t cite much of the preceding literature suggests there’s a problem, but it’s unclear exactly what the problem is.
A study from ACM suggests that selectivity — both being selective and being known as selective — has a citation benefit.
Is there a good case against linking? Or are links just an updated version of an old idea?
Scientists appear to be reading more AND citing less. Are these two findings compatible?