However, we identify three drawbacks of this approach. First,
significant curated text input data in the target language are
required; second, output topics require expert interpretation; and
third, the ATAM algorithm has several parameters that require
expert tuning. That is, in order to adapt the algorithm to a new
location and/or language, expertise in both machine learning as
well as the target language are required.