@inproceedings{rai-etal-2022-identifying,
title = "Identifying Human Needs through Social Media: A study on {I}ndian cities during {COVID}-19",
author = "Rai, Sunny and
Joseph, Rohan and
Thakur, Prakruti Singh and
Khaliq, Mohammed Abdul",
editor = "Ku, Lun-Wei and
Li, Cheng-Te and
Tsai, Yu-Che and
Wang, Wei-Yao",
booktitle = "Proceedings of the Tenth International Workshop on Natural Language Processing for Social Media",
month = jul,
year = "2022",
address = "Seattle, Washington",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.socialnlp-1.6",
doi = "10.18653/v1/2022.socialnlp-1.6",
pages = "65--74",
abstract = "In this paper, we present a minimally-supervised approach to identify human needs expressed in tweets. Taking inspiration from Frustration-Aggression theory, we trained RoBERTa model to classify tweets expressing frustration which serves as an indicator of unmet needs. Although the notion of frustration is highly subjective and complex, the findings support the use of pretrained language model in identifying tweets with unmet needs. Our study reveals the major causes behind feeling frustrated during the lockdown and the second wave of the COVID-19 pandemic in India. Our proposed approach can be useful in timely identification and prioritization of emerging human needs in the event of a crisis.",
}
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<abstract>In this paper, we present a minimally-supervised approach to identify human needs expressed in tweets. Taking inspiration from Frustration-Aggression theory, we trained RoBERTa model to classify tweets expressing frustration which serves as an indicator of unmet needs. Although the notion of frustration is highly subjective and complex, the findings support the use of pretrained language model in identifying tweets with unmet needs. Our study reveals the major causes behind feeling frustrated during the lockdown and the second wave of the COVID-19 pandemic in India. Our proposed approach can be useful in timely identification and prioritization of emerging human needs in the event of a crisis.</abstract>
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%0 Conference Proceedings
%T Identifying Human Needs through Social Media: A study on Indian cities during COVID-19
%A Rai, Sunny
%A Joseph, Rohan
%A Thakur, Prakruti Singh
%A Khaliq, Mohammed Abdul
%Y Ku, Lun-Wei
%Y Li, Cheng-Te
%Y Tsai, Yu-Che
%Y Wang, Wei-Yao
%S Proceedings of the Tenth International Workshop on Natural Language Processing for Social Media
%D 2022
%8 July
%I Association for Computational Linguistics
%C Seattle, Washington
%F rai-etal-2022-identifying
%X In this paper, we present a minimally-supervised approach to identify human needs expressed in tweets. Taking inspiration from Frustration-Aggression theory, we trained RoBERTa model to classify tweets expressing frustration which serves as an indicator of unmet needs. Although the notion of frustration is highly subjective and complex, the findings support the use of pretrained language model in identifying tweets with unmet needs. Our study reveals the major causes behind feeling frustrated during the lockdown and the second wave of the COVID-19 pandemic in India. Our proposed approach can be useful in timely identification and prioritization of emerging human needs in the event of a crisis.
%R 10.18653/v1/2022.socialnlp-1.6
%U https://aclanthology.org/2022.socialnlp-1.6
%U https://doi.org/10.18653/v1/2022.socialnlp-1.6
%P 65-74
Markdown (Informal)
[Identifying Human Needs through Social Media: A study on Indian cities during COVID-19](https://aclanthology.org/2022.socialnlp-1.6) (Rai et al., SocialNLP 2022)
ACL