AI Article Synopsis
- Social data plays a crucial role in disaster management, particularly in healthcare and tracking the COVID-19 pandemic.
- This study focuses on analyzing Facebook posts in seven languages to monitor COVID-19 trends, offering a different perspective compared to previous works largely relying on Twitter.
- The research involved a detailed analytics process from data gathering to topic modeling, revealing that the identified topics aligned with the chronological changes in pandemic discourse and responses across different languages and countries.
Article Abstract
Social data has shown important role in tracking, monitoring and risk management of disasters. Indeed, several works focused on the benefits of social data analysis for the healthcare practices and curing domain. Similarly, these data are exploited now for tracking the COVID-19 pandemic but the majority of works exploited Twitter as source. In this paper, we choose to exploit Facebook, rarely used, for tracking the evolution of COVID-19 related trends. In fact, a multilingual dataset covering 7 languages (English (EN), Arabic (AR), Spanish (ES), Italian (IT), German (DE), French (FR) and Japanese (JP)) is extracted from Facebook public posts. The proposal is an analytics process including a data gathering step, pre-processing, LDA-based topic modeling and presentation module using graph structure. Data analysing covers the duration spanned from January 1st, 2020 to May 15, 2020 divided on three periods in cumulative way: first period January-February, second period March-April and the last one to 15 May. The results showed that the extracted topics correspond to the chronological development of what has been circulated around the pandemic and the measures that have been taken according to the various languages under discussion representing several countries.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7881346 | PMC |
| http://dx.doi.org/10.1007/s10489-020-02033-3 | DOI Listing |
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