Unlink the link between COVID-19 and 5G Networks: an NLP and SNA based approach
Issue Date
2020-11-18Subjects
5G mobile communicationsocial networking
coherence
5G conspiracy
topic modelling
radiation scare
corona-5G link
pandemics
analytical models
blogs
tweet analysis
Subject Categories::P304 Electronic Media studies
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Social 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.Citation
Bahja M, Safdar GA (2020) 'Unlink the link between COVID-19 and 5G Networks: an NLP and SNA based approach', IEEE Access, 8Journal
IEEE AccessAdditional Links
https://ieeexplore.ieee.org/document/9262907Type
ArticleLanguage
enISSN
2169-3536EISSN
2169-3536ae974a485f413a2113503eed53cd6c53
10.1109/ACCESS.2020.3039168
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