  Sarcasm is a form of irony that involves saying or writing something that is
opposite or opposite to what one really means, often in a humorous or mocking
way. It is often used to mock or mock someone or something, or to be humorous
or amusing. Sarcasm is usually conveyed through tone of voice, facial
expressions, or other forms of nonverbal communication, but it can also be
indicated by the use of certain words or phrases that are typically associated
with irony or humor. Sarcasm detection is difficult because it relies on
context and non-verbal cues. It can also be culturally specific, subjective and
ambiguous. In this work, we fine-tune the RoBERTa based sarcasm detection model
presented in Abaskohi et al. [2022] to get to within 0.02 F1 of the
state-of-the-art (Hercog et al. [2022]) on the iSarcasm dataset (Oprea and
Magdy [2019]). This performance is achieved by augmenting iSarcasm with a
pruned version of the Self Annotated Reddit Corpus (SARC) (Khodak et al.
[2017]). Our pruned version is 100 times smaller than the subset of SARC used
to train the state-of-the-art model.
