Conference paper Open Access

Topics and sentiments on Twitter during lockdown in London

Cui, Nan; Malleson, Nick; Comber, Alexis

The aim of this study is to investigate the topics that people discussed in Greater London during the Coronavirus disease 2019 (COVID-19) lockdown period. The Latent Dirichlet Allocation (LDA) method was used to investigate the topics discussed by people, then the sentiments and perceptions of social media users were evaluated by using Syuzhet R package, and the spatial patterns of urban green space visitation were also studied. LDA analysis identified eight topic groups, among which the word “lockdown” was frequently mentioned. Further, the sentiment analysis showed that users posted Tweets that were more negative when they referred to ‘lockdown’ during this period.

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