Test Policy Parser for News Data

[TimBMK]

See if generating Terms via Twitter Data (Seeds only or both Seeds and Walk Terms) yields good results for classifying News Data

[marcoggithub]

First evaluation: Results look quite promising overall, but there are some problems here and there:

• quantile_cutoff does not work, since score_norm is the better quality indicator
• raw_score does not work at all to show how a document is ranked, therefore score_norm (doc) has the best results
• there needs to be a cut_off by score_norm as well (very liberal = 0.7, IMO: On a first glance should be more around 0.8 to 0.9)
• A minimun of returned documents (around 50) should be considered as well, because of a steep drop in score_norm values
• Some policy fields seem to have worse results more often than others: entwicklung, soziales (sometimes umwelt), there should at least only show documents with a score_norm of 1
• Some policy fields contain a lot of corona documents, but the walk terms (most often) seem fine and IMO it often makes sense (aeusseres, eruopa, arbeit, etc..)
• Found one case in umwelt and soziales, where the walk terms could be better