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.