Sarcasm Detection and Building an E nglish Language Corpus in Real Time (2021)

Abstract: This is a research proposal for doctoral research into sarcasm detection, and the real-time compilation of an English language corpus of sarcastic utterances. It details the previous research into similar topics, the potential research directions and the research aims.

## introduction within the discipline of computational linguistics, and specifically in the field of sentiment analysis, sarcasm detection is a fast-growing area of research. in the past twelve months alone there have been multiple papers written on the subject of sarcasm and irony detection @xcite @xcite . sarcasm detection uses natural language processing models along with sentiment analysis based on linguistic cues such as hyperbole or polarity shifts, as well as context to decode whether or not an utterance is sarcastic. @xcite give the example of "great! i love waking up sick!", which is easy for a human to detect as sarcastic due to "strong polarity shifts", but would remain a challenge for a machine. suggested applications for research into sarcasm detection include improving the understanding of users' or customers' emotions and opinions about policies, products or services for businesses and governments or policy-makers @xcite . ## aims of the study to summarise the aims and focus of this research, there are two current aims which will be the main focus of the research. they are as follows: the first aim is to try and tackle the issue of a lack of large and up-to-date corpora to provide training data for detection algorithms and models. the second is to attempt to improve the current detection rates, particularly on natural data that is unrelated to the training set. there are also two potential further research directions that may be undertaken depending on the eventual feasibility of introducing other areas of research. these aims are the following: these additional directions would be to attempt to expand into areas of sarcasm detection that currently have had little to no research conducted into them.