News & Events

Assessing post-disaster recovery using sentiment analysis: The case of L’Aquila,

Memorial days of disasters represent an opportunity to evaluate the progress of recovery.  April 6 2019, was the 10th anniversary of the earthquake in L'Aquila, Italy. We have processed and analysed 4349 tweets collected from 4 to 10 April 2019 with the hashtag: # L'Aquila. This article uses sentiment analysis (SA) to assess post-disaster recovery on the 10th anniversary of L'Aquila's earthquake using Twitter data. Sentiment analysis is a natural language processing (NLP) method to automatically analyse text data through sentiments, emotions and opinions about a specific topic. This NPL method has been mainly used for customer reviews of products and places (restaurants and hotels). In this research, we used SA to evaluate L'Aquila's recovery progress because we conceive post-disaster recovery as a service provided by governments to their citizens as customers. Further analysis of the tweets confirms that after 10 years, the reconstruction is still ongoing and that criticism of the recovery reported in the literature is also found in the tweets. Additional information is presented in our publication:

The dataset with the Twitter data is available for public consultation at:

  • Contreras Mojica, Diana; Wilkinson, Sean; Balan, Nipun; James, Philip (2021): Polarity supervised classification of Twitter data related to the 10th anniversary of the L'Aquila 2009 earthquake. Newcastle University. Dataset. 

Last modified: Sun, 15 Aug 2021 19:28:14 BST