Assessment of urban air quality from Twitter communication using self-attention network and a multilayer classification model.

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_2.5

SUBMITTER: Kumbalaparambi TS 

PROVIDER: S-EPMC9453714 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature