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Lookup NU author(s): Professor Sean WilkinsonORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2025 by the authors. The 2010 Haiti earthquake stands as one of the most catastrophic events in terms of loss of life and destruction. Following an earthquake, there is an urgent demand for information. Regrettably, few studies have tracked the progress of the post-disaster recovery, leaving this phase poorly understood. In previous years, data were exclusively collected through on-site missions, but today, social media (SM) has enhanced earthquake reconnaissance teams’ capacity to collect data beyond the emergency phase. However, text data from SM is unstructured, making it necessary to use natural language processing techniques to extract meaningful information. Sentiment analysis (SA), which classifies people’s opinions into positive, negative, or neutral polarity, is a promising tool for understanding earthquake recovery. For the purposes of this paper, we conduct SA at the tweet level on data collected around the tenth anniversary of the earthquake using human expertise to fine-tune automatic classification methods. We conclude that the anniversary date is the best time to collect data. In our sample, 56.3% of the tweets in the sample were classified as negative, followed by positive (27.3%), neutral (8.2%), and unrelated (8.1%). In our study, we conclude that the assessment of the recovery progress based on data collected from Twitter is negative. The automatic method for SA with the highest accuracy is ‘btweet’. The assessment result must be validated by stakeholders.
Author(s): Contreras D, Antypas D, Hervas J, Wilkinson S, Camacho-Collados J, Garnier P, Cornou C
Publication type: Article
Publication status: Published
Journal: Sustainability
Year: 2025
Volume: 17
Issue: 11
Online publication date: 28/05/2025
Acceptance date: 02/05/2025
Date deposited: 09/07/2025
ISSN (electronic): 2071-1050
Publisher: MDPI
URL: https://doi.org/10.3390/su17114967
DOI: 10.3390/su17114967
Data Access Statement: Contreras, Diana; Antypas, Dimosthenis; Camacho-Collados, Jose; Wilkinson, Sean (2022): Comparative sentiment analysis (SA) of original Twitter data posted in English about the 10th anniversary of the 2010 Haiti Earthquake. Newcastle University. Dataset. https://doi.org/10.25405/data.ncl.19688040.v3. Contreras, Diana; Hervas, Javier; Balan, Nipun; James, Philip (2022): Sentiment analysis (supervised and unsupervised classification) of original Twitter data posted in English about the 10th anniversary of the 2010 Haiti Earthquake. Newcastle University. Dataset. https://doi.org/10.25405/data.ncl.19478021.v1.
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