id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-351065-nyfnwrtm	Zhang, Tenghao	Integrating GIS technique with Google Trends data to analyse COVID-19 severity and public interest	2020-09-16		.txt	text/plain	460	40	61	title: Integrating GIS technique with Google Trends data to analyse COVID-19 severity and public interest Some studies suggest that health related issues can cause anxiety which may lead to increased public attention, typically manifested by online information search. Adams et al.'s (2020) GIS-based study points out the shortcomings of using unnormalized COVID-19 demographic data in choropleth mapping, and their use of the normalized data (confirmed cases per 100,000 people) presents a more accurate visualisation of pandemic severity. The COVID-19 case data were retrieved from the US health authority (https://cdc.gov/covid-datatracker). Public interest was captured by people's Google search data in each state. 7 The data were acquired from the Google Trends service, which uses a normalized relative search volume The role of health anxiety in online health information search The disguised pandemic: The importance of data normalization in COVID-19 web mapping	./cache/cord-351065-nyfnwrtm.txt	./txt/cord-351065-nyfnwrtm.txt