The Effect of Sociocultural Variables on Sarcasm Communication Online
Not on the map. Why?
Abstract (arXiv)
Online social networks (OSN) play an essential role for connecting people and allowing them to communicate online. OSN users share their thoughts, moments, and news with their network. The messages they share online can include sarcastic posts, where the intended meaning expressed by the written text is different from the literal one. This could result in miscommunication. Previous research in psycholinguistics has studied the sociocultural factors the might lead to sarcasm misunderstanding between speakers and listeners. However, there is a lack of such studies in the context of OSN. In this paper we fill this gap by performing a quantitative analysis on the influence of sociocultural variables, including gender, age, country, and English language nativeness, on the effectiveness of sarcastic communication online. We collect examples of sarcastic tweets directly from the authors who posted them. Further, we ask third-party annotators of different sociocultural backgrounds to label these tweets for sarcasm. Our analysis indicates that age, English language nativeness, and country are significantly influential and should be considered in the design of future social analysis tools that either study sarcasm directly, or look at related phenomena where sarcasm may have an influence. We also make observations about the social ecology surrounding sarcastic exchanges on OSNs. We conclude by suggesting ways in which our findings can be included in future work.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Apr 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2023: 2; 2024: 0; 2025: 2; 2026: 1.
5 papers.
- 2023A Survey on Out-of-Distribution Evaluation of Neural NLP Modelscited by 20
- 2025Culture is Everywhere: A Call for Intentionally Cultural Evaluationcited by 10
- 2023Dimensions of Online Conflict: Towards Modeling Agonismcited by 2
- 2026The Consensus Trap: Dissecting Subjectivity and the "Ground Truth" Illusion in Data Annotationcited by 1
- 2025Nek Minit: Harnessing Pragmatic Metacognitive Prompting for Explainable Sarcasm Detection of Australian and Indian Englishcited by 0
- 2026The Consensus Trap: Dissecting Subjectivity and the "Ground Truth" Illusion in Data Annotation11 Feb 2026
- 2025Culture is Everywhere: A Call for Intentionally Cultural Evaluation1 Sep 2025
- 2025Nek Minit: Harnessing Pragmatic Metacognitive Prompting for Explainable Sarcasm Detection of Australian and Indian English21 May 2025
- 2023Dimensions of Online Conflict: Towards Modeling Agonism6 Nov 2023
- 2023A Survey on Out-of-Distribution Evaluation of Neural NLP Models27 Jun 2023