Embedding Projection for Targeted Cross-Lingual Sentiment:Model Comparisons and a Real-World Study
Table 3: Number of aspect-polarity tuples for the targeted datasets.
['[EMPTY]', '[EMPTY]', 'Binary +', 'Binary −', 'Multiclass ++', 'Multiclass +', 'Multiclass 0', 'Multiclass −', 'Multiclass −−']
4.1.2 Targeted Datasets We use the following corpora to set up the experiments in which we train on a source language corpus CS and test on a target language corpus CT. We include a binary classification setup, where neutral has been removed and strong positive and strong negative have been mapped to positive and negative, as well as a multiclass setup, where the original labels are used. Similarly, models do not learn the Strong Negative class on the OpeNER and MultiBooked datasets.