RESUMEN
Purpose: First, the key vulnerability factors from the literature are identified. Second, using the vulnerability factors as indicators, a composite index is developed. Last, from the index values, a set of vulnerability knowledge maps, showing the vulnerability hotspots, are prepared. Design/methodology/approach: This study aims to develop a pandemic vulnerability knowledge visualisation index to support the strategic decision-making efforts of authorities. Findings: Ten indicators are identified as vulnerability factors that could significantly impact the virus spread risks. Verifying the identified hotspots against the recorded infected cases and deaths has evidenced the usefulness of the index. Determining and visualising the high-vulnerability locations and communities could help in informed strategic decision-making and responses of the authorities to the pandemic. Originality/value: The study demonstrates that the developed pandemic vulnerability knowledge visualisation index is particularly appropriate in the context of Australia. Nonetheless, by replicating the methodologic steps of the study, customised versions can be developed for other country contexts. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
RESUMEN
BACKGROUND AND OBJECTIVES: Due to COVID-19, various countries introduced lockdowns and limited citizen movements. These restrictions triggered an increased use of digital technologies and platforms by the public. This provides an opportunity for the authorities to capture public perceptions on COVID-19 from social media channels to make informed decisions. The use of social media analytics during pandemics for decision-making, however, is an understudied area of research. Thus, this study aims to generate insights into how social media analytics can assist authorities in pandemic-related policy decisions. METHODS: This study involved a social media analysis approach-i.e., systematic geo-Twitter analysis-that contains descriptive, content, sentiment, and spatial analyses. Australian states and territories are selected as the case study context for the empirical investigation. This study collected 96,666 geotagged tweets (originated from Australia between 1 January and 4 May 2020), and analysed 35,969 of them after data cleaning. RESULTS: The findings disclose that: (a) Social media analytics is an efficient approach to capture the attitudes and perceptions of the public during a pandemic; (b) Crowdsourced social media data can guide interventions and decisions of the authorities during a pandemic, and; (c) Effective use of government social media channels can help the public to follow the introduced measures/restrictions. CONCLUSION: The findings are invaluable for authorities to understand community perceptions and identify communities in needs and demands in a pandemic situation, where authorities are not in a position to conduct direct and lengthily public consultations.