  On December 31st 2019, the World Health Organization (WHO) China Country
Office was informed of cases of pneumonia of unknown etiology detected in Wuhan
City. The cause of the syndrome was a new type of coronavirus isolated on
January 7th 2020 and named Severe Acute Respiratory Syndrome CoronaVirus 2
(SARS-CoV-2). SARS-CoV-2 is the cause of the coronavirus disease 2019
(COVID-19). Since January 2020 an ever increasing number of scientific works
have appeared in literature. Identifying relevant research outcomes at very
early stages is challenging. In this work we use COVID-19 as a use-case for
investigating: (i) which tools and frameworks are mostly used for early
scholarly communication; (ii) to what extent altmetrics can be used to identify
potential impactful research in tight (i.e. quasi-zero-day) time-windows. A
literature review with rigorous eligibility criteria is performed for gathering
a sample composed of scientific papers about SARS-CoV-2/COVID-19 appeared in
literature in the tight time-window ranging from January 15th 2020 to February
24th 2020. This sample is used for building a knowledge graph that represents
the knowledge about papers and indicators formally. This knowledge graph feeds
a data analysis process which is applied for experimenting with altmetrics as
impact indicators. We find moderate correlation among traditional citation
count, citations on social media, and mentions on news and blogs. This suggests
there is a common intended meaning of the citational acts associated with
aforementioned indicators. Additionally, we define a method that harmonises
different indicators for providing a multi-dimensional impact indicator.
