Tecnolengua Lingmotif at EmoInt-2017: A lexicon-based approach
Antonio Moreno Ortiz · 2017
In this paper we describe Tecnolengua Group's participation in the shared task on emotion intensity at WASSA 2017.We used the Lingmotif tool and a new, complementary tool, Lingmotif Learn, which we developed for this occasion.We based our intensity predictions for the four test datasets entirely on Lingmotif's TSS (text sentiment score) feature.We also developed mechanisms for dealing with the idiosyncrasies of Twitter text.Results were comparatively poor, but the experience meant a good opportunity for us to identify issues in our score calculation for short texts, a genre for which the Lingmotif tool was not originally designed.* This research was supported by Spain's MINECO through the funding of project Lingmotif2 (FFI2016-78141-P). 1 We use the term short text to refer specifically to under 140 characters, such as those used in Twitter and other social networks.