Rapid detection of fast innovation under the pressure of COVID-19
Nicola Melluso, Andrea Bonaccorsi, Filippo Chiarello, Gualtiero, Fantoni

TL;DR
This paper introduces a new method for quickly detecting technological convergence during COVID-19 by analyzing data from Medium, revealing rapid shifts in innovation related to remote work, health, and learning.
Contribution
It proposes a novel hybrid social media-based approach for rapid detection of technological convergence, addressing limitations of traditional patent and publication indicators.
Findings
Detected rapid technological shifts in remote control, health, and remote learning.
Demonstrated Medium as an effective source for real-time innovation monitoring.
Compared network structures before and after COVID-19 to identify convergence phenomena.
Abstract
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…
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Taxonomy
TopicsGenetics, Bioinformatics, and Biomedical Research · COVID-19 diagnosis using AI · Biomedical and Engineering Education
