Having a look at the new WMF research site, I noticed that it seems that notification and recommendations mechanisms are the key strategy being focused on re. the filling of Wikipedia's content gaps. Having just finished a research project on just this problem and coming to the opposite conclusion i.e. that automated mechanisms were insufficient for solving the gaps problem, I was curious to find out more.
This latest research that I was involved in with colleagues was based on an action research project aiming to fill gaps in topics relating to South Africa. The team tried a range of different strategies discussed in the literature for filling Wikipedia's gaps without any wild success. Automated mechanisms that featured missing and incomplete articles catalysed very few edits.
When looking for related research, it seemed that others had come to a similar conclusion i.e. that automated notification/recommendations alone didn't lead to improvements in particular target areas. That makes me think that a) I just haven't come across the right research or b) that there are different types of gaps and that those different types require different solutions i.e. the difference between filling gaps across language versions, gaps created by incomplete articles about topics for which there are few online/reliable sources is different from the lack of articles about topics for which there are many online/reliable sources, gaps in articles about particular topics, relating to particular geographic areas etc.
Does anyone have any insight here? - either on research that would help practitioners decide how to go about a project of filling gaps in a particular subject area or about whether the key focus of research at the WMF is on filling gaps via automated means such as recommendation and notification mechanisms?
Many thanks!
Best, Heather.