Detecting sarcasm from students' feedback in Twitter

Nabeela Altrabsheh; Mihaela Cocea; Sanaz Fallahkhair

doi:10.1007/978-3-319-24258-3_57

Detecting sarcasm from students' feedback in Twitter

Nabeela Altrabsheh, Mihaela Cocea, Sanaz Fallahkhair

University of Brighton

Research output: Chapter in Book/Conference proceeding with ISSN or ISBN › Conference contribution with ISSN or ISBN › peer-review

Abstract

Sarcasm is a sophisticated form of act where one says or writes the opposite of what they mean. Sarcasm is a common issue in sentiment analysis and detecting it is a challenge. While models for sarcasm detection have been proposed for general purposes (e.g. Twitter data, Amazon reviews), there is no research addressing this issue in an educational context, despite the increased use of social media in education. In this paper we experiment with several machine learning techniques, features and preprocessing levels to identify sarcasm from students' feedback collected via Twitter.

Original language	English
Title of host publication	10th European Conference on Technology Enhanced Learning, EC-TEL
Place of Publication	Toledo, Spain
Publisher	Springer
Pages	551-555
Number of pages	5
Volume	9307
DOIs	https://doi.org/10.1007/978-3-319-24258-3_57
Publication status	Published - 14 Sept 2015
Event	10th European Conference on Technology Enhanced Learning, EC-TEL - Toledo, Spain, 15-18 Sep 2015 Duration: 14 Sept 2015 → …

Publication series

Name	Lecture Notes in Computer Science

Conference

Conference	10th European Conference on Technology Enhanced Learning, EC-TEL
Period	14/09/15 → …

Bibliographical note

The final publication is available at link.springer.com

Access to Document

10.1007/978-3-319-24258-3_57Licence: Unspecified

ECTEL15 after submission.pdfAccepted author manuscript, 116 KBLicence: Unspecified

Sanaz Fallahkhair
- S.Fallahkhairbrighton.acuk
- School of Arch, Tech and Eng - Principal Lecturer
- Computing and Mathematical Sciences Research and Enterprise Group
Person: Academic

Cite this

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title = "Detecting sarcasm from students' feedback in Twitter",

abstract = "Sarcasm is a sophisticated form of act where one says or writes the opposite of what they mean. Sarcasm is a common issue in sentiment analysis and detecting it is a challenge. While models for sarcasm detection have been proposed for general purposes (e.g. Twitter data, Amazon reviews), there is no research addressing this issue in an educational context, despite the increased use of social media in education. In this paper we experiment with several machine learning techniques, features and preprocessing levels to identify sarcasm from students' feedback collected via Twitter.",

author = "Nabeela Altrabsheh and Mihaela Cocea and Sanaz Fallahkhair",

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Altrabsheh, N, Cocea, M & Fallahkhair, S 2015, Detecting sarcasm from students' feedback in Twitter. in 10th European Conference on Technology Enhanced Learning, EC-TEL. vol. 9307, Lecture Notes in Computer Science, Springer, Toledo, Spain, pp. 551-555, 10th European Conference on Technology Enhanced Learning, EC-TEL, 14/09/15. https://doi.org/10.1007/978-3-319-24258-3_57

Detecting sarcasm from students' feedback in Twitter. / Altrabsheh, Nabeela; Cocea, Mihaela; Fallahkhair, Sanaz.
10th European Conference on Technology Enhanced Learning, EC-TEL. Vol. 9307 Toledo, Spain: Springer, 2015. p. 551-555 (Lecture Notes in Computer Science).

Research output: Chapter in Book/Conference proceeding with ISSN or ISBN › Conference contribution with ISSN or ISBN › peer-review

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T1 - Detecting sarcasm from students' feedback in Twitter

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AU - Cocea, Mihaela

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PY - 2015/9/14

Y1 - 2015/9/14

N2 - Sarcasm is a sophisticated form of act where one says or writes the opposite of what they mean. Sarcasm is a common issue in sentiment analysis and detecting it is a challenge. While models for sarcasm detection have been proposed for general purposes (e.g. Twitter data, Amazon reviews), there is no research addressing this issue in an educational context, despite the increased use of social media in education. In this paper we experiment with several machine learning techniques, features and preprocessing levels to identify sarcasm from students' feedback collected via Twitter.

AB - Sarcasm is a sophisticated form of act where one says or writes the opposite of what they mean. Sarcasm is a common issue in sentiment analysis and detecting it is a challenge. While models for sarcasm detection have been proposed for general purposes (e.g. Twitter data, Amazon reviews), there is no research addressing this issue in an educational context, despite the increased use of social media in education. In this paper we experiment with several machine learning techniques, features and preprocessing levels to identify sarcasm from students' feedback collected via Twitter.

U2 - 10.1007/978-3-319-24258-3_57

DO - 10.1007/978-3-319-24258-3_57

M3 - Conference contribution with ISSN or ISBN

VL - 9307

T3 - Lecture Notes in Computer Science

SP - 551

EP - 555

BT - 10th European Conference on Technology Enhanced Learning, EC-TEL

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T2 - 10th European Conference on Technology Enhanced Learning, EC-TEL

Y2 - 14 September 2015

ER -

Detecting sarcasm from students' feedback in Twitter

Abstract

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Sanaz Fallahkhair

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