Abstract
AbstractGoogle Trends (GT) offers a historical database of global internet searches with the potential to complement conventional records of environmental hazards, especially in regions where formal hydrometeorological data are scarce. We evaluate the extent to which GT can discern heavy rainfall and floods in Kenya and Uganda during the period 2014 to 2018. We triangulate counts of flood searches from GT with available rainfall records and media reports to build an inventory of extreme events. The Spearman rank correlation (ρ) between monthly mean search interest for flooding and monthly Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) rainfall totals was ρ = +0.38 (p < 0.005) for Kenya and ρ = +0.64 (p < 0.001) for Uganda. Media reports of flooding were used to specify a threshold of detectability to give the same overall frequency of floods based on GT search interest. When the GT search index threshold was set at ≥15 and ≥29, the correct detection rate was 75% and 64% within a five‐day window of known flood events in Kenya and Uganda, respectively. From these preliminary explorations we conclude that GT has potential as a proxy data source, but greater skill may emerge in places with larger search volumes and by linking to historical information about environmental hazards at sub‐national scales. Wider applicability of the GT platform might be possible if there is greater transparency about how Google algorithms determine topics.
Highlights
Use of Big Data has exploded thanks to increasing computer processing power, falling storage costs, and improving accessibility to software
In Kenya, peaks in search interest coincided with notable floods decayed over time as flood waters receded
We investigated the feasibility of using Google Trends (GT) to analyse historical floods
Summary
Use of Big Data has exploded thanks to increasing computer processing power, falling storage costs, and improving accessibility to software. Google has a 95% market share in Kenya and Uganda based on volume of searches compared with other search engine platforms like Bing, Firefox, and Internet Explorer (Statcounter, 2019). Google Trends is a publicly available sample of search data that are anonymised, categorised, and aggregated across all Google products, including YouTube (Google Trends, 2019) This allows users to gauge interest in a search term or topic by period and domain (even to city‐scale for countries with sufficient search volumes). Data are presented as a proportion of all searches on all topics on Google for the specified period and location This accounts for changing numbers of internet users through time. A correct detection is when the search threshold and daily interest value signal a flood within a specified number of days of the observed flood; false detection is when the search interest is above the threshold, suggesting a flood, yet none was captured by the media within the specified period
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