  Covid-19 has rapidly redefined the agenda of technological research and
development both for academics and practitioners. If the medical scientific
publication system has promptly reacted to this new situation, other domains,
particularly in new technologies, struggle to map what is happening in their
contexts. The pandemic has created the need for a rapid detection of
technological convergence phenomena, but at the same time it has made clear
that this task is impossible on the basis of traditional patent and publication
indicators. This paper presents a novel methodology to perform a rapid
detection of the fast technological convergence phenomenon that is occurring
under the pressure of the Covid-19 pandemic. The fast detection has been
performed thanks to the use of a novel source: the online blogging platform
Medium. We demonstrate that the hybrid structure of this social journalism
platform allows a rapid detection of innovation phenomena, unlike other
traditional sources. The technological convergence phenomenon has been modelled
through a network-based approach, analysing the differences of networks
computed during two time periods (pre and post COVID-19). The results led us to
discuss the repurposing of technologies regarding "Remote Control", "Remote
Working", "Health" and "Remote Learning".
