A Linguistic Annotation Framework to Study Interactions in Multilingual Healthcare Conversational Forums

Ishani Mondal, Kalika Bali, Mohit Jain, Monojit Choudhury, Ashish Sharma, Evans Gitau, Jacki O’Neill, Kagonya Awori, Sarah Gitau


Abstract
In recent years, remote digital healthcare using online chats has gained momentum, especially in the Global South. Though prior work has studied interaction patterns in online (health) forums, such as TalkLife, Reddit and Facebook, there has been limited work in understanding interactions in small, close-knit community of instant messengers. In this paper, we propose a linguistic annotation framework to facilitate analysis of health-focused WhatsApp groups. The primary aim of the framework is to understand interpersonal relationships among peer supporters in order to help develop NLP solutions for remote patient care and reduce burden of overworked healthcare providers. Our framework consists of fine-grained peer support categorization and message-level sentiment tagging. Additionally, due to the prevalence of code-mixing in such groups, we incorporate word-level language annotations. We use the proposed framework to study two WhatsApp groups in Kenya for youth living with HIV, facilitated by a healthcare provider.
Anthology ID:
2021.law-1.7
Volume:
Proceedings of The Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop
Month:
November
Year:
2021
Address:
Punta Cana, Dominican Republic
Venues:
DMR | EMNLP | LAW
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
66–77
Language:
URL:
https://aclanthology.org/2021.law-1.7
DOI:
10.18653/v1/2021.law-1.7
Bibkey:
Cite (ACL):
Ishani Mondal, Kalika Bali, Mohit Jain, Monojit Choudhury, Ashish Sharma, Evans Gitau, Jacki O’Neill, Kagonya Awori, and Sarah Gitau. 2021. A Linguistic Annotation Framework to Study Interactions in Multilingual Healthcare Conversational Forums. In Proceedings of The Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop, pages 66–77, Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
A Linguistic Annotation Framework to Study Interactions in Multilingual Healthcare Conversational Forums (Mondal et al., LAW 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.law-1.7.pdf