Detecting sarcasm from students' feedback in Twitter

Nabeela Altrabsheh, Mihaela Cocea, Sanaz Fallahkhair

Research output: Chapter in Book/Conference proceeding with ISSN or ISBNConference contribution with ISSN or ISBN

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 languageEnglish
Title of host publication10th European Conference on Technology Enhanced Learning, EC-TEL
Place of PublicationToledo, Spain
PublisherSpringer
Pages551-555
Number of pages5
Volume9307
DOIs
Publication statusPublished - 14 Sep 2015
Event10th European Conference on Technology Enhanced Learning, EC-TEL - Toledo, Spain, 15-18 Sep 2015
Duration: 14 Sep 2015 → …

Publication series

NameLecture Notes in Computer Science

Conference

Conference10th European Conference on Technology Enhanced Learning, EC-TEL
Period14/09/15 → …

Bibliographical note

The final publication is available at link.springer.com

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  • Cite this

    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, pp. 551-555). (Lecture Notes in Computer Science). Springer. https://doi.org/10.1007/978-3-319-24258-3_57