ArticleEnvironmental science and pollution research international2023
Assessment of urban air quality from Twitter communication using self-attention network and a multilayer classification model.
Article in Environmental science and pollution research international, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Mapping respiratory health digital interventions in South and Southeast Asia: a scoping review.Journal of global health · 2025Article
- A GIS-based approach to determining optimal location for decentralized inner city smart filters: Toward net zero cities.Heliyon · 2024Article
- Breathing together: A global hashtag analysis of #LungHealth on platform X (formerly Twitter).Digital healthArticle
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Authors and funding
4 authors.
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Abstract
Social media platforms are one of the prominent new-age methods used by public for spreading awareness or drawing attention on an issue or concern. This study demonstrates how the twitter responses of public can be used for qualitative monitoring of air pollution in an urban area. Tweets discussing about air quality in Delhi, India, were extracted during 2019-2020 using a machine learning technique based on self-attention network. These tweets were cleaned, sorted, and classified into 3-class quality viz. poor air quality, good air quality, and noise or neutral tweets. The present study used a multilayer classification model with first layer as an embedding layer and second layer as bi-directional long-short term memory (BiLSTM) layer. A method was then devised for estimating PM
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