@inproceedings{mondal-etal-2022-language,
title = "Language Patterns and Behaviour of the Peer Supporters in Multilingual Healthcare Conversational Forums",
author = "Mondal, Ishani and
Bali, Kalika and
Jain, Mohit and
Choudhury, Monojit and
O{'}Neill, Jacki and
Ochieng, Millicent and
Awori, Kagnoya and
Ronen, Keshet",
editor = "Calzolari, Nicoletta and
B{\'e}chet, Fr{\'e}d{\'e}ric and
Blache, Philippe and
Choukri, Khalid and
Cieri, Christopher and
Declerck, Thierry and
Goggi, Sara and
Isahara, Hitoshi and
Maegaard, Bente and
Mariani, Joseph and
Mazo, H{\'e}l{\`e}ne and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
month = jun,
year = "2022",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2022.lrec-1.102",
pages = "963--975",
abstract = "In this work, we conduct a quantitative linguistic analysis of the language usage patterns of multilingual peer supporters in two health-focused WhatsApp groups in Kenya comprising of youth living with HIV. Even though the language of communication for the group was predominantly English, we observe frequent use of Kiswahili, Sheng and code-mixing among the three languages. We present an analysis of language choice and its accommodation, different functions of code-mixing, and relationship between sentiment and code-mixing. To explore the effectiveness of off-the-shelf Language Technologies (LT) in such situations, we attempt to build a sentiment analyzer for this dataset. Our experiments demonstrate the challenges of developing LT and therefore effective interventions for such forums and languages. We provide recommendations for language resources that should be built to address these challenges.",
}
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<abstract>In this work, we conduct a quantitative linguistic analysis of the language usage patterns of multilingual peer supporters in two health-focused WhatsApp groups in Kenya comprising of youth living with HIV. Even though the language of communication for the group was predominantly English, we observe frequent use of Kiswahili, Sheng and code-mixing among the three languages. We present an analysis of language choice and its accommodation, different functions of code-mixing, and relationship between sentiment and code-mixing. To explore the effectiveness of off-the-shelf Language Technologies (LT) in such situations, we attempt to build a sentiment analyzer for this dataset. Our experiments demonstrate the challenges of developing LT and therefore effective interventions for such forums and languages. We provide recommendations for language resources that should be built to address these challenges.</abstract>
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%0 Conference Proceedings
%T Language Patterns and Behaviour of the Peer Supporters in Multilingual Healthcare Conversational Forums
%A Mondal, Ishani
%A Bali, Kalika
%A Jain, Mohit
%A Choudhury, Monojit
%A O’Neill, Jacki
%A Ochieng, Millicent
%A Awori, Kagnoya
%A Ronen, Keshet
%Y Calzolari, Nicoletta
%Y Béchet, Frédéric
%Y Blache, Philippe
%Y Choukri, Khalid
%Y Cieri, Christopher
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Isahara, Hitoshi
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Hélène
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Thirteenth Language Resources and Evaluation Conference
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F mondal-etal-2022-language
%X In this work, we conduct a quantitative linguistic analysis of the language usage patterns of multilingual peer supporters in two health-focused WhatsApp groups in Kenya comprising of youth living with HIV. Even though the language of communication for the group was predominantly English, we observe frequent use of Kiswahili, Sheng and code-mixing among the three languages. We present an analysis of language choice and its accommodation, different functions of code-mixing, and relationship between sentiment and code-mixing. To explore the effectiveness of off-the-shelf Language Technologies (LT) in such situations, we attempt to build a sentiment analyzer for this dataset. Our experiments demonstrate the challenges of developing LT and therefore effective interventions for such forums and languages. We provide recommendations for language resources that should be built to address these challenges.
%U https://aclanthology.org/2022.lrec-1.102
%P 963-975
Markdown (Informal)
[Language Patterns and Behaviour of the Peer Supporters in Multilingual Healthcare Conversational Forums](https://aclanthology.org/2022.lrec-1.102) (Mondal et al., LREC 2022)
ACL
- Ishani Mondal, Kalika Bali, Mohit Jain, Monojit Choudhury, Jacki O’Neill, Millicent Ochieng, Kagnoya Awori, and Keshet Ronen. 2022. Language Patterns and Behaviour of the Peer Supporters in Multilingual Healthcare Conversational Forums. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 963–975, Marseille, France. European Language Resources Association.