Sarcasm detection on Twitter

Date
2016-05
Authors
Lyu, Hao
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract

State-of-the-art approaches for sarcasm detection in social media combine lexical clues with contextual information surrounding the potentially sarcastic posting including author information. This article presents detailed methods for performing contextualizing sarcasm detection on Twitter, including data extraction, feature engineering and classification model settings. I reproduce the state-of-the-art results reported by Bamman and Smith (2015).

Department
Description
Citation