TY - JOUR
T1 - You don’t say... Linguistic features in sarcasm detection
AU - Ducret, Martina
AU - Kruse, Lauren
AU - Martinez, Carlos
AU - Feldman, Anna
AU - Peng, Jing
N1 - Publisher Copyright:
Copyright © 2020 for this paper by its authors.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020
Y1 - 2020
N2 - We explore linguistic features that contribute to sarcasm detection. The linguistic features that we investigate are a combination of text and word complexity, stylistic and psychological features. We experiment with sarcastic tweets with and without context. The results of our experiments indicate that contextual information is crucial for sarcasm prediction. One important observation is that sarcastic tweets are typically incongruent with their context in terms of sentiment or emotional load.
AB - We explore linguistic features that contribute to sarcasm detection. The linguistic features that we investigate are a combination of text and word complexity, stylistic and psychological features. We experiment with sarcastic tweets with and without context. The results of our experiments indicate that contextual information is crucial for sarcasm prediction. One important observation is that sarcastic tweets are typically incongruent with their context in terms of sentiment or emotional load.
UR - http://www.scopus.com/inward/record.url?scp=85097894605&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:85097894605
SN - 1613-0073
VL - 2769
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
T2 - 7th Italian Conference on Computational Linguistics, CLiC-it 2020
Y2 - 1 March 2021 through 3 March 2021
ER -