COVID-19 Image Search Queries
Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)
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Title |
COVID-19 Image Search Queries
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Identifier |
https://doi.org/10.7910/DVN/QWFTYD
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Creator |
Orphanou, Kalia
Christoforou, Evgenia Otterbarcher, Jahna Paramita Lestari, Monica Hopfgartner, Frank |
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Publisher |
Harvard Dataverse
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Description |
The unprecedented events of the COVID-19 pandemic have generated an enormous amount of information and populated the Web with new content relevant to the pandemic and its implications. Images are often interpreted as being closer to the truth as compared to other forms of communication, because of their physical representation of an event such as the COVID-19 pandemic. This dataset includes the image search queries related to the first wave of pandemic, provided by crowdworkers across four regions of Europe that were severely affected by the first wave of pandemic (UK, Germany, Italy, Spain). To collect the queries, we run two crowdsourcing tasks as also described in the paper. The dataset includes the merging of the queries from both tasks for each of the four countries. We identified all the unique queries collected from the participants in each country and computed the number of appearances for each unique query without considering any duplicates of the same user, i.e. frequency.
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Subject |
Computer and Information Science
Social Sciences Crowdsourcing, image search queries, COVID-19 |
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Contributor |
Otterbacher, Jahna
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