Paper Abstract and Keywords |
Presentation |
2015-07-29 09:25
Sarcasm Detection
-- How to Identify Sarcastic Statements in Twitter -- Mondher Bouazizi, Tomoaki Ohtsuki (Keio Univ.) ASN2015-21 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Sarcasm is a special form of speech by which the person conveys implicit information, within the message he transmits. Sarcasm is widely used in social networks and microblogging websites such as Twitter, where people criticize or give remarks in a way that makes it difficult even for humans to tell if what is said is what is meant. Recognizing sarcastic statements can be very useful to improve automatic sentiment analysis of data collected from the net. It helps also enhance the efficiency of after-sales services by understanding the real intentions and opinions of consumers when browsing their feedback or complaints. In this article we propose a method for sarcasm detection in Twitter. We identify the different types of sarcasm used in social networks. We propose four sets of features that cover these types of sarcasm, and that will be used to classify tweets into sarcastic and non-sarcastic. We evaluate the performances of our approach. We study the importance of each set of features and evaluate its importance in the classification. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Twitter / sarcasm detection / sentiment analysis / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 115, no. 162, ASN2015-21, pp. 7-12, July 2015. |
Paper # |
ASN2015-21 |
Date of Issue |
2015-07-22 (ASN) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
Download PDF |
ASN2015-21 |
Conference Information |
Committee |
RCC ASN RCS NS SR |
Conference Date |
2015-07-29 - 2015-07-31 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
JA Naganoken Bldg. |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Wireless Distributed Network, M2M: Machine-to-Machine, D2D (Device-to-Device),etc. |
Paper Information |
Registration To |
ASN |
Conference Code |
2015-07-RCC-ASN-RCS-NS-SR |
Language |
English |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Sarcasm Detection |
Sub Title (in English) |
How to Identify Sarcastic Statements in Twitter |
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Twitter |
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sarcasm detection |
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sentiment analysis |
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1st Author's Name |
Mondher Bouazizi |
1st Author's Affiliation |
Keio University (Keio Univ.) |
2nd Author's Name |
Tomoaki Ohtsuki |
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Keio University (Keio Univ.) |
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Speaker |
Author-1 |
Date Time |
2015-07-29 09:25:00 |
Presentation Time |
25 minutes |
Registration for |
ASN |
Paper # |
ASN2015-21 |
Volume (vol) |
vol.115 |
Number (no) |
no.162 |
Page |
pp.7-12 |
#Pages |
6 |
Date of Issue |
2015-07-22 (ASN) |
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