The Non-native Speaker Aspect: Indian English in Social Media

Rupak Sarkar, Sayantan Mahinder, Ashiqur KhudaBukhsh


Abstract
As the largest institutionalized second language variety of English, Indian English has received a sustained focus from linguists for decades. However, to the best of our knowledge, no prior study has contrasted web-expressions of Indian English in noisy social media with English generated by a social media user base that are predominantly native speakers. In this paper, we address this gap in the literature through conducting a comprehensive analysis considering multiple structural and semantic aspects. In addition, we propose a novel application of language models to perform automatic linguistic quality assessment.
Anthology ID:
2020.wnut-1.9
Volume:
Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020)
Month:
November
Year:
2020
Address:
Online
Editors:
Wei Xu, Alan Ritter, Tim Baldwin, Afshin Rahimi
Venue:
WNUT
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
61–70
Language:
URL:
https://aclanthology.org/2020.wnut-1.9
DOI:
10.18653/v1/2020.wnut-1.9
Bibkey:
Cite (ACL):
Rupak Sarkar, Sayantan Mahinder, and Ashiqur KhudaBukhsh. 2020. The Non-native Speaker Aspect: Indian English in Social Media. In Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020), pages 61–70, Online. Association for Computational Linguistics.
Cite (Informal):
The Non-native Speaker Aspect: Indian English in Social Media (Sarkar et al., WNUT 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.wnut-1.9.pdf