Parallel Deep Learning-Driven Sarcasm Detection from Pop Culture Text and English Humor Literature

06/10/2021
by   Sourav Das, et al.
0

Sarcasm is a sophisticated way of wrapping any immanent truth, mes-sage, or even mockery within a hilarious manner. The advent of communications using social networks has mass-produced new avenues of socialization. It can be further said that humor, irony, sarcasm, and wit are the four chariots of being socially funny in the modern days. In this paper, we manually extract the sarcastic word distribution features of a benchmark pop culture sarcasm corpus, containing sarcastic dialogues and monologues. We generate input sequences formed of the weighted vectors from such words. We further propose an amalgamation of four parallel deep long-short term networks (pLSTM), each with distinctive activation classifier. These modules are primarily aimed at successfully detecting sarcasm from the text corpus. Our proposed model for detecting sarcasm peaks a training accuracy of 98.95 discussed dataset. Consecutively, it obtains the highest of 98.31 validation accuracy on two handpicked Project Gutenberg English humor literature among all the test cases. Our approach transcends previous state-of-the-art works on several sarcasm corpora and results in a new gold standard performance for sarcasm detection.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/03/2021

Sexism detection: The first corpus in Algerian dialect with a code-switching in Arabic/ French and English

In this paper, an approach for hate speech detection against women in Ar...
research
12/03/2019

An Annotated Dataset of Coreference in English Literature

We present in this work a new dataset of coreference annotations for wor...
research
04/10/2019

Detecting Cybersecurity Events from Noisy Short Text

It is very critical to analyze messages shared over social networks for ...
research
04/03/2017

Cascaded Segmentation-Detection Networks for Word-Level Text Spotting

We introduce an algorithm for word-level text spotting that is able to a...
research
01/30/2023

A Human Word Association based model for topic detection in social networks

With the widespread use of social networks, detecting the topics discuss...
research
09/26/2020

ARPA: Armenian Paraphrase Detection Corpus and Models

In this work, we employ a semi-automatic method based on back translatio...

Please sign up or login with your details

Forgot password? Click here to reset