Paper: Humans Require Context to Infer Ironic Intent (so Computers Probably do, too)

ACL ID P14-2084
Title Humans Require Context to Infer Ironic Intent (so Computers Probably do, too)
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

Automatically detecting verbal irony (roughly, sarcasm) is a challenging task because ironists say something other than ? and often opposite to ? what they actually mean. Discerning ironic intent exclusively from the words and syntax comprising texts (e.g., tweets, forum posts) is therefore not always possible: additional contextual information about the speaker and/or the topic at hand is often necessary. We introduce a new corpus that provides empirical evidence for this claim. We show that annota- tors frequently require context to make judgements concerning ironic intent, and that machine learning approaches tend to misclassify those same comments for which annotators required additional context.