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Recent Trends In Sarcasm Detection on Online Social Networks

K.Ranganath 1 , MD.Sallauddin 2 , Shabana 3

  1. Computer Science and Engineering, Sumathi Reddy Institute of Technology for Women, JNTU Hyderabad, Warangal, India.
  2. Computer science and Engineering, SR Engineering College, Hyderabad, Warangal, India.
  3. Computer Science and Engineering, Sumathi Reddy Institute of Technology for Women, JNTU Hyderabad, Warangal, India.

Correspondence should be addressed to: ranga1kanakam@gmail.com.

Section:Review Paper, Product Type: Journal Paper
Volume-5 , Issue-10 , Page no. 235-239, Oct-2017

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v5i10.235239

Online published on Oct 30, 2017

Copyright © K.Ranganath, MD.Sallauddin, Shabana . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: K.Ranganath, MD.Sallauddin, Shabana , “Recent Trends In Sarcasm Detection on Online Social Networks,” International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.235-239, 2017.

MLA Style Citation: K.Ranganath, MD.Sallauddin, Shabana "Recent Trends In Sarcasm Detection on Online Social Networks." International Journal of Computer Sciences and Engineering 5.10 (2017): 235-239.

APA Style Citation: K.Ranganath, MD.Sallauddin, Shabana , (2017). Recent Trends In Sarcasm Detection on Online Social Networks. International Journal of Computer Sciences and Engineering, 5(10), 235-239.

BibTex Style Citation:
@article{_2017,
author = {K.Ranganath, MD.Sallauddin, Shabana },
title = {Recent Trends In Sarcasm Detection on Online Social Networks},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {10 2017},
volume = {5},
Issue = {10},
month = {10},
year = {2017},
issn = {2347-2693},
pages = {235-239},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1504},
doi = {https://doi.org/10.26438/ijcse/v5i10.235239}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v5i10.235239}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1504
TI - Recent Trends In Sarcasm Detection on Online Social Networks
T2 - International Journal of Computer Sciences and Engineering
AU - K.Ranganath, MD.Sallauddin, Shabana
PY - 2017
DA - 2017/10/30
PB - IJCSE, Indore, INDIA
SP - 235-239
IS - 10
VL - 5
SN - 2347-2693
ER -

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Abstract

Online Social Networks become largest platform to express people feelings, opinions, views and real time events such as live tweets etc. Example Twitter has 315 million monthly active users, eighty two percent of active users on mobile and millions of tweets are being circulated through twitter every day. Various organizations as well as companies are interested in twitter data for finding the views of various people towards their products or events. Sarcasm refers to expressing negative feelings using positive words. To detect sarcasm among those tweets is comparatively more difficult. This paper discussed various approaches to find sarcasm on twitter. With the help of sarcasm detection, companies could analyze the feelings of user about their products. This is helpful for companies, as the companies could improve their quality of product.

Key-Words / Index Term

Sarcasm, Sarcasm detection, Twitter

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