Sarcasm Detection from Social Media Posts using Machine-learning Techniques: A Comparative Analysis

Mariya Siddiqui, Rajnish Pandey, Shobhit Srivastava, Ramapati Mishra, Nalini Singh

2021

Abstract

Social media is a platform where everyone from each age group is interested in posting their daily activities. A customer, post reviews about a product he bought, a person who is a victim of some natural disasters, post their current situations, and in other scenarios too, the people use these social media platforms to post their feelings. Getting the correct sentiments of these posts is one of the most challenging tasks ever. The presence of a sarcastic tweet may hinder the texts' actual meaning. In this paper, we have collected sarcastic tweets from Twitter and validated this Dataset with the help of different conventional machine learning classifiers. The support vector machine performed better and achieved an F1-score of 0.84

Paper Citation

in Harvard Style

Siddiqui M., Pandey R., Srivastava S., Mishra R. and Singh N. (2021). Sarcasm Detection from Social Media Posts using Machine-learning Techniques: A Comparative Analysis. In Proceedings of the 3rd International Conference on Advanced Computing and Software Engineering - Volume 1: ICACSE, ISBN 978-989-758-544-9, pages 28-33. DOI: 10.5220/0010561900003161

in Bibtex Style

@conference{icacse21,
author={Mariya Siddiqui and Rajnish Pandey and Shobhit Srivastava and Ramapati Mishra and Nalini Singh},
title={Sarcasm Detection from Social Media Posts using Machine-learning Techniques: A Comparative Analysis},
booktitle={Proceedings of the 3rd International Conference on Advanced Computing and Software Engineering - Volume 1: ICACSE,},
year={2021},
pages={28-33},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010561900003161},
isbn={978-989-758-544-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Advanced Computing and Software Engineering - Volume 1: ICACSE,
TI - Sarcasm Detection from Social Media Posts using Machine-learning Techniques: A Comparative Analysis
SN - 978-989-758-544-9
AU - Siddiqui M.
AU - Pandey R.
AU - Srivastava S.
AU - Mishra R.
AU - Singh N.
PY - 2021
SP - 28
EP - 33
DO - 10.5220/0010561900003161