Monday mornings are my fave : ) #not Exploring the Automatic Recognition of Irony in English tweets

Cynthia Van Hee, Els Lefever, Véronique Hoste
2016 International Conference on Computational Linguistics  
Recognising and understanding irony is crucial for the improvement natural language processing tasks including sentiment analysis. In this study, we describe the construction of an English Twitter corpus and its annotation for irony based on a newly developed fine-grained annotation scheme. We also explore the feasibility of automatic irony recognition by exploiting a varied set of features including lexical, syntactic, sentiment and semantic (Word2Vec) information. Experiments on a held-out
more » ... t set show that our irony classifier benefits from this combined information, yielding an F 1 -score of 67.66%. When explicit hashtag information like #irony is included in the data, the system even obtains an F 1 -score of 92.77%. A qualitative analysis of the output reveals that recognising irony that results from a polarity clash appears to be (much) more feasible than recognising other forms of ironic utterances (e.g., descriptions of situational irony).
dblp:conf/coling/HeeLH16 fatcat:r2wjc6fgovfqrbeakyzaexuqe4