Abstract: This paper presents computational work to detect satire/sarcasm in long commentaries on Italian politics. It uses the lexica extracted from the manual annotation based on Appraisal Theory, of some 30K word texts. The underlying hypothesis is that using this framework it is possible to precisely pinpoint ironic content through the deep semantic analysis of evaluative judgement and appreciation. The paper presents the manual annotation phase realized on 112 texts by two well-known Italian journalists. After a first experimentation phase based on the lexica extracted from the xml output files, we proceeded to retag lexical entries dividing them up into two subclasses: figurative and literal meaning. Finally more fine-grained Appraisal features have been derived and more experiments have been carried out and compared to results obtained by a lean sentiment analysis. The final output is produced from held out texts to verify the usefulness of the lexica and the Appraisal theory in detecting ironic content.
Delmonte & Stingo REF presented a computational work whose intention was to detect satire/sarcasm in long commentaries on Italian politics.
Detecting Satire in Italian Political Commentaries
ICCCI
Computer Science