IIIDYT at IEST 2018: Implicit Emotion Classification With Deep Contextualized Word Representations
Table 5: Fine grained performance on tweets containing emoji, and the effect of removing them.
['[BOLD] Emoji alias', '[BOLD] N', '[BOLD] emoji #', '[BOLD] emoji %', '[BOLD] no-emoji #', '[BOLD] no-emoji %', '[BOLD] Δ%']
Table 5 shows the effect specific emoji have on classification performance. [CONTINUE] It is clear some emoji strongly contribute to improving prediction quality. [CONTINUE] The most interesting ones are mask, rage, and cry, which significantly increase accuracy. [CONTINUE] Further, contrary to intuition, the sob emoji contributes less than cry, despite representing a stronger emotion. [CONTINUE] Finally, not all emoji are beneficial for this task. [CONTINUE] When removing sweat smile and confused accuracy increased,