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dc.contributor.authorBahja, Mohammed
dc.contributor.authorSafdar, Ghazanfar Ali
dc.date.accessioned2021-07-19T11:24:04Z
dc.date.available2020-11-18T00:00:00Z
dc.date.available2021-07-19T11:24:04Z
dc.date.issued2020-11-18
dc.identifier.citationBahja M, Safdar GA (2020) 'Unlink the link between COVID-19 and 5G Networks: an NLP and SNA based approach', IEEE Access, 8en_US
dc.identifier.issn2169-3536
dc.identifier.doi10.1109/ACCESS.2020.3039168
dc.identifier.urihttp://hdl.handle.net/10547/625057
dc.description.abstractSocial media facilitates rapid dissemination of information for both factual and fictional information. The spread of non-scientific information through social media platforms such as Twitter has potential to cause damaging consequences. Situations such as the COVID-19 pandemic provides a favourable environment for misinformation to thrive. The upcoming 5G technology is one of the recent victims of misinformation and fake news and has been plagued with misinformation about the effects of its radiation. During the COVID-19 pandemic, conspiracy theories linking the cause of the pandemic to 5G technology have resonated with a section of people leading to outcomes such as destructive attacks on 5G towers. The analysis of the social network data can help to understand the nature of the information being spread and identify the commonly occurring themes in the information. The natural language processing (NLP) and the statistical analysis of the social network data can empower policymakers to understand the misinformation being spread and develop targeted strategies to counter the misinformation. In this paper, NLP based analysis of tweets linking COVID-19 to 5G is presented. NLP models including Latent Dirichlet allocation (LDA), sentiment analysis (SA) and social network analysis (SNA) were applied for the analysis of the tweets and identification of topics. An understanding of the topic frequencies, the inter-relationships between topics and geographical occurrence of the tweets allows identifying agencies and patterns in the spread of misinformation and equips policymakers with knowledge to devise counter-strategies.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.urlhttps://ieeexplore.ieee.org/document/9262907en_US
dc.rightsGreen - can archive pre-print and post-print or publisher's version/PDF
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subject5G mobile communicationen_US
dc.subjectsocial networkingen_US
dc.subjectcoherenceen_US
dc.subject5G conspiracyen_US
dc.subjecttopic modellingen_US
dc.subjectradiation scareen_US
dc.subjectcorona-5G linken_US
dc.subjectpandemicsen_US
dc.subjectanalytical modelsen_US
dc.subjectblogsen_US
dc.subjecttweet analysisen_US
dc.subjectSubject Categories::P304 Electronic Media studiesen_US
dc.titleUnlink the link between COVID-19 and 5G Networks: an NLP and SNA based approachen_US
dc.typeArticleen_US
dc.identifier.eissn2169-3536
dc.contributor.departmentUniversity of Birminghamen_US
dc.contributor.departmentUniversity of Bedfordshireen_US
dc.identifier.journalIEEE Accessen_US
dc.date.updated2021-07-19T11:20:26Z
dc.description.notegold open access


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