The First French COVID19 Lockdown Twitter Dataset

Autor:	Balech, Sophie, Benavent, Christophe, Calciu, Mihai
Rok vydání:	2020
Předmět:	Computer Science - Social and Information Networks J.4
Druh dokumentu:	Working Paper
Popis:	In this paper, we present a mainly French coronavirus Twitter dataset that we have been continuously collecting since lockdown restrictions have been enacted in France (in March 17, 2020). We offer our datasets and sentiment analysis annotations to the research community at https://github.com/calciu/COVID19-LockdownFr. They have been obtained using high performance computing (HPC) capabilities of our university's datacenter. We think that our contribution can facilitate analysis of online conversation dynamics reflecting people sentiments when facing severe home confinement restrictions determined by the outbreak of this world wide epidemic. We hope that our contribution will help decode shared experience and mood but also test the sensitivity of sentiment measurement instruments and incite the development of new instruments, methods and approaches. Comment: 6 pages, 1 figure, 4 tables
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2005.05075 Zobrazit plný text záznamu View this record from Arxiv