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Accuracy of a pre-trained sentiment analysis (SA) classification model on tweets related to emergency response and early recovery assessment: the case of 2019 Albanian earthquake

Crossref DOI link: https://doi.org/10.1007/s11069-022-05307-w

Published Online: 2022-03-23

Published Print: 2022-08

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Contreras, Diana https://orcid.org/0000-0003-2852-6015
Wilkinson, Sean

Alterman, Evangeline https://orcid.org/0000-0001-5942-3866
Hervás, Javier https://orcid.org/0000-0003-4272-3525
Funding

Funding for this research was provided by:

engineering and physical sciences research council (EP/P025641/1)
License Information

Text and Data Mining valid from 2022-03-23

Version of Record valid from 2022-03-23
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Article History

Received: 22 July 2021

Accepted: 24 February 2022

First Online: 23 March 2022

Declarations

:

: Authors declare neither conflict of interest nor competing interest.

: Regulations regarding General Data Protection Regulation (GDPR) were observed in the database published. The team of information security of Newcastle University approved the publication of the database only after the Twitter handle from users were removed to avoid their traceability and protect their privacy.

: All authors have agreed to participate in the manuscript.

: All authors have given their consent to publish the current version of the manuscript.

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