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Visual analytics of twitter and social media dataflows: A casestudy of COVID-19 rumors

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dc.contributor.authorGrigorieva, M. A.
dc.contributor.authorUlizko, M. S.
dc.contributor.authorAntonov, E. V.
dc.contributor.authorTretyakov, E. S.
dc.contributor.authorTukumbetova, R. R.
dc.contributor.authorArtamonov, A. A.
dc.contributor.authorУлизко, Михаил Сергеевич
dc.contributor.authorАнтонов, Евгений Вячеславович
dc.contributor.authorТукумбетова, Руфина Рашитовна
dc.contributor.authorАртамонов, Алексей Анатольевич
dc.date.accessioned2024-11-30T00:05:28Z
dc.date.available2024-11-30T00:05:28Z
dc.date.issued2021
dc.description.abstract© 2021 National Research Nuclear University. All rights reserved.One of the most significant and rapidly developing fields of data analysis is information flow management. In the course of the analysis targeted and stochastic dissemination patterns are studied. The solving of such problems is daunting due to the global growth of the amount of information and its availability for a wide range of users. The paper presents a study of dissemination of information in open networks on the example of COVID-19. The study was conducted with the use of web scraping, methods of linguistic analysis and visual analytics. As sources of information variety of sources were used, such as the largest world and Russian information services, social networks and instant messengers. The paper considers statistical analysis of English media articles and posts form Twitter, dissemination of data flows between countries and information source. The developed methods can be scaled up to analyse information events of various topics.
dc.format.extentС. 144-163
dc.identifier.citationVisual analytics of twitter and social media dataflows: A casestudy of COVID-19 rumors / Grigorieva, M.A. [et al.] // Scientific Visualization. - 2021. - 13. - № 4. - P. 144-163. - 10.26583/sv.13.4.11
dc.identifier.doi10.26583/sv.13.4.11
dc.identifier.urihttps://www.doi.org/10.26583/sv.13.4.11
dc.identifier.urihttps://www.scopus.com/record/display.uri?eid=2-s2.0-85119615065&origin=resultslist
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/25052
dc.relation.ispartofScientific Visualization
dc.titleVisual analytics of twitter and social media dataflows: A casestudy of COVID-19 rumors
dc.typeArticle
dspace.entity.typePublication
oaire.citation.issue4
oaire.citation.volume13
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