Influencers and covid_19: Characterizing and defining courses of action
Romain Boulet () and
Additional contact information
Romain Boulet: Centre de Recherche Magellan - UJML - Université Jean Moulin - Lyon 3 - Université de Lyon - Institut d'Administration des Entreprises (IAE) - Lyon
Post-Print from HAL
Based upon the 55 days of lockdown that occurred during the Covid_19 disaster, the aim of this article is to answer to the following research question: "how can we characterize influencers in social networks?". Analyzing more than 1.6 million of tweets, we propose a matrix that can be used to characterize an influencer. This matrix has 2 dimensions on one hand the five courses of actions an influencer can use and on the other hand the 3 types of motivation he has got. Regarding the methodology we used R and a qualitative content analysis and provided our scripts. This research is a part of the "lockdown lab" project
Keywords: COVID19; Influence; Social Network; Twitter (search for similar items in EconPapers)
Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-02871287
References: Add references at CitEc
Citations: Track citations by RSS feed
Published in Management & Data Science, Management & Data Science, 2020, 4 (4)
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:halshs-02871287
Access Statistics for this paper
More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().