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Covid19/IT the digital side of Covid19: A picture from Italy with clustering and taxonomy.
Bonnici, Vincenzo; Cicceri, Giovanni; Distefano, Salvatore; Galletta, Letterio; Polignano, Marco; Scaffidi, Carlo.
  • Bonnici V; Università degli Studi di Parma, Parma, Italy.
  • Cicceri G; Università degli Studi di Messina, Messina, Italy.
  • Distefano S; Università degli Studi di Messina, Messina, Italy.
  • Galletta L; Scuola IMT Alti Studi Lucca, Lucca, Italy.
  • Polignano M; Università degli Studi di Bari Aldo Moro, Bari, Italy.
  • Scaffidi C; Università degli Studi di Messina, Messina, Italy.
PLoS One ; 17(6): e0269687, 2022.
Article in English | MEDLINE | ID: covidwho-2021796
ABSTRACT
The Covid19 pandemic has significantly impacted on our lives, triggering a strong reaction resulting in vaccines, more effective diagnoses and therapies, policies to contain the pandemic outbreak, to name but a few. A significant contribution to their success comes from the computer science and information technology communities, both in support to other disciplines and as the primary driver of solutions for, e.g., diagnostics, social distancing, and contact tracing. In this work, we surveyed the Italian computer science and engineering community initiatives against the Covid19 pandemic. The 128 responses thus collected document the response of such a community during the first pandemic wave in Italy (February-May 2020), through several initiatives carried out by both single researchers and research groups able to promptly react to Covid19, even remotely. The data obtained by the survey are here reported, discussed and further investigated by Natural Language Processing techniques, to generate semantic clusters based on embedding representations of the surveyed activity descriptions. The resulting clusters have been then used to extend an existing Covid19 taxonomy with the classification of related research activities in computer science and information technology areas, summarizing this work contribution through a reproducible survey-to-taxonomy methodology.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Randomized controlled trials Topics: Vaccines Limits: Humans Country/Region as subject: Europa Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2022 Document Type: Article Affiliation country: Journal.pone.0269687

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Randomized controlled trials Topics: Vaccines Limits: Humans Country/Region as subject: Europa Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2022 Document Type: Article Affiliation country: Journal.pone.0269687