A Simple Approach to Multilingual Polarity Classification in Twitter
(e) B4MSA’s performance summary; the last columns correspond to three standard scores.
['name', '[EMPTY]', 'language', 'classes', 'challenge’s score', 'rank', 'score', 'acc.', 'macro  [ITALIC] F1', '( [ITALIC] Fpos1+ [ITALIC] Fneg1)/2']
The performance corresponds to the multilingual set of features, i.e., we do not used language-dependent techniques. The remaining two contests correspond to the SemEval’15-16. To be consistent with the rest of the experiments, B4MSA uses only the official training set. The results can be significantly improved using larger training datasets; for example, joining SemEval’13