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Chapter 13 - Social Network Analysis Techniques Using NodeXL for Analyzing Disinformation Related to QAnon

from Part IV - The Role of Communication in Promoting and Limiting QAnon Support

Published online by Cambridge University Press:  14 September 2023

By
Wasim Ahmed  and
Marc Smith
Edited by
Monica K. Miller
Monica K. Miller
Affiliation:
University of Nevada, Reno
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Summary

Researchers have investigated how disinformation and fake news spreads through social networks. Understanding how disinformation flows on social networks can help identify interventions to reduce the impact of such falsehoods and prevent negative consequences that can result from following conspiracy theories. This chapter will provide an overview of how researchers can use the tool NodeXL to rapidly analyse social media data related to QAnon by drawing upon social network analysis. NodeXL can be used to identify the shape of the network, key opinion leaders, and content related to discussions around QAnon. NodeXL was recently utilised to study disinformation networks surrounding COVID-19, such as the 5G and COVID-19 conspiracy and the ‘Film Your Hospital’ conspiracy. The chapter will also examine how the QAnon Twitter network compares to other Twitter networks. The chapter will then provide an insight into future potential research avenues that could be pursued by scholars working in this area.

Keywords

Social MediaTwitterNodeXLNetwork AnalysisDisinformation
Type
Chapter
Information
The Social Science of QAnon
A New Social and Political Phenomenon
 , pp. 216 - 233
Publisher: Cambridge University Press
Print publication year: 2023

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References

Ahmed, W. (2021, May 18). Using Twitter as a data source: An overview of social media research tools (updated for 2021). Impact of Social Sciences Blog. https://blogs.lse.ac.uk/impactofsocialsciences/2021/05/18/using-twitter-as-a-data-source-an-overview-of-social-media-research-tools-2021/Google Scholar
Ahmed, W., & Lugovic, S. (2019). Social media analytics: Analysis and visualisation of news diffusion using NodeXL. Online Information Review, 43(4), 149–160.Google Scholar
Ahmed, W., Bath, P. A., Sbaffi, L., & Demartini, G. (2018). Moral panic through the lens of Twitter: An analysis of infectious disease outbreaks. In Proceedings of the 9th International Conference on Social Media and Society (pp. 217–221). Association for Computing Machinery.Google Scholar
Ahmed, W., Fenton, A., Hardey, M., & Das, R. (2022). Binge watching and the role of social media virality towards promoting Netflix’s Squid Game. IIM Kozhikode Society & Management Review, 11(2), 222–234.Google Scholar
Ahmed, W., Seguí, F. L., Vidal-Alaball, J., & Katz, M. S. (2020a). COVID-19 and the “Film Your Hospital” conspiracy theory: Social network analysis of twitter data. Journal of Medical Internet Research, 22(10), e22374.Google Scholar
Ahmed, W., Vidal-Alaball, J., Downing, J., & Seguí, F. L. (2020b). COVID-19 and the 5G conspiracy theory: Social network analysis of Twitter data. Journal of Medical Internet Research, 22(5), e19458.CrossRefGoogle ScholarPubMed
Clauset, A., Newman, M. E. J., & Moore, C. (2004). Finding community structure in very large networks. Physical Review E, 70, 066111.CrossRefGoogle ScholarPubMed
Cline, D. H. (1993). Six degrees of Alexander: Social network analysis as a tool for ancient history. www.ancienthistorybulletin.org/subscribed-users-area/wp-content/uploads/2015/04/DIANE-HARRIS-CLINE-Six-Degrees-of-Alexander-Social-Network-Analysis-as-a-Tool-for-Ancient-History-Volume-26-59-70.pdfGoogle Scholar
Das, R., & Ahmed, W. (2022). Rethinking fake news: Disinformation and ideology during the time of COVID-19 global pandemic. IIM Kozhikode Society & Management Review, 11(1), 146–159.Google Scholar
Hameleers, M., Brosius, A., Marquart, F., Goldberg, A. C., van Elsas, E., & de Vreese, C. H. (2022). Mistake or manipulation? Conceptualizing perceived mis- and disinformation among news consumers in 10 European countries. Communication Research, 49(7), 919–941.Google Scholar
Himelboim, I., Smith, M. A., Rainie, L., Shneiderman, B., & Espina, C. (2017). Classifying Twitter topic-networks using social network analysis. Social Media + Society, 3(1), 2056305117691545.CrossRefGoogle Scholar
Jordan, K. (2020). Imagined audiences, acceptable identity fragments and merging the personal and professional: How academic online identity is expressed through different social media platforms. Learning, Media and Technology, 45(2), 165–178.CrossRefGoogle Scholar
Koren, Y., & Harel, D. (2003). Axis-by-axis stress minimization. In International Symposium on Graph Drawing (pp. 450–459). Springer.Google Scholar
Olszowski, R., Zabdyr-Jamróz, M., Baran, S., Pięta, P., & Ahmed, W. (2022). A social network analysis of tweets related to mandatory COVID-19 vaccination in Poland. Vaccines, 10(5), 750.CrossRefGoogle ScholarPubMed
Smith, M. A. (2015). Catalyzing social media scholarship with open tools and data. Journal of Contemporary Eastern Asia, 14(2), 87–96.Google Scholar
Smith, M. A., Himelboim, I., Rainie, L., & Shneiderman, B. (2015). The structures of Twitter crowds and conversations. In Matei, S. A., Russell, M. G., & Bertino, E. (Eds.), Transparency in social media (pp. 67–108). Springer.Google Scholar

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