Irony and Sarcasm: Corpus Generation and Analysis Using Crowdsourcing

  • Filatova E
  • 126

    Readers

    Mendeley users who have this article in their library.
  • 52

    Citations

    Citations of this article.

Abstract

Abstract The ability to reliably identify sarcasm and irony in text can improve the performance of many Natural Language Processing (NLP) systems including summarization, sentiment analysis, etc. The existing sarcasm detection systems have focused on identifying sarcasm on a sentence level or for a specific phrase. However, often it is impossible to identify a sentence containing sarcasm without knowing the context. In this paper we describe a corpus generation experiment where we collect regular and sarcastic Amazon product reviews. We perform qualitative and quantitative analysis of the corpus. The resulting corpus can be used for identifying sarcasm on two levels: a document and a text utterance (where a text utterance can be as short as a sentence and as long as a whole document).

Author-supplied keywords

  • corpus
  • product reviews
  • sarcasm

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document

Authors

  • Elena Filatova

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free