Within the NLP community, Best-Worst Scaling (BWS) has thus far been used only to annotate words: for example, for creating datasets for relational similarity (Jurgens et al., 2012), word-sense disambiguation (Jurgens, 2013), word-sentiment intensity (Kiritchenko et al., 2014), and phrase sentiment composition (Kiritchenko and Mohammad, 2016).
a promising avenue of future work is to test theories of emotion composition: e.g, whether optimism is indeed a combination of joy and anticipation, whether awe if fear and surprise, and so on, as some have suggested (Plutchik, 1980).