IronyMagnet at SemEval-2018 Task 3: A Siamese network for Irony detection in Social media

Aniruddha Ghosh,Tony Veale

doi:10.18653/v1/s18-1093

Abstract

This paper describes our system, entitled IronyMagnet, for the 3rd Task of the SemEval 2018 workshop, “Irony Detection in English Tweets”. In Task 1, irony classification task has been considered as a binary classification task. Now for the first time, finer categories of irony are considered as part of a shared task. In task 2, three types of irony are considered; “Irony by contrast” - ironic instances where evaluative expression portrays inverse polarity (positive, negative) of the literal proposition; “Situational irony” - ironic instances where output of a situation do not comply with its expectation; “Other verbal irony” - instances where ironic intent does not rely on polarity contrast or unexpected outcome. We proposed a Siamese neural network for irony detection, which is consisted of two subnetworks, each containing a long short term memory layer(LSTM) and an embedding layer initialized with vectors from Glove word embedding 1 . The system achieved a f-score of 0.72, and 0.50 in task 1, and task 2 respectively.

Highlights

Irony is one of the most prominent and pervasive figures of speech in human communication, dating back to ancient religious texts to modern microtexts
Ironic utterances from as early as childhood (Harris and Pexman, 2003). Such capabilities are often associated with one’s ability to correctly infer others’ communicative intentions and perspectives towards a given situation. Psychological theories, such as “echoic reminder theory” (Kreuz and Glucksberg, 1989), “allusion pretense theory” (Kumon-Nakamura et al, 1995), and “implicit display theory” (Utsumi, 2000), confirm that cues for understanding ironic intent are not restricted to language
As a purely text classification task, the irony detection task poses a significant challenge for computational linguists

Summary

Introduction

Irony is one of the most prominent and pervasive figures of speech in human communication, dating back to ancient religious texts to modern microtexts. According to literary scholars (Grice, 1978; Lakoff, 1993), irony has been defined as a trope where the speaker intends to communicate a contradictory situation or the opposite meaning of what is literally said It adopts a subtle technique where incongruity is used to suggest a distinction between reality and expectation in order to produce a humorous or emphatic effect on the listener. Ironic utterances from as early as childhood (Harris and Pexman, 2003) Such capabilities are often associated with one’s ability to correctly infer others’ communicative intentions and perspectives towards a given situation. An ironic statement starts with an overtly positive attitude (“Yay I love”) and ends up in an disappointment (“working on my birthday”) or a negative attitude/statement (“another outage in less than 8 hours.”) followed by an appreciation (“Keep up the good work!”) or an incident (“I asked God to protect me from my enemies”) resulting in a completely unexpected output (“shortly after I started losing friends”)

Methods

Results

Conclusion