Comparing Social Media Communities using Functional Data Analysis

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dc.contributor.authorChampon, Xiaoxia
dc.contributor.authorJayalath, Chathura
dc.contributor.authorRand, William
dc.contributor.authorJasser, Jasser
dc.contributor.authorGaribay , Ivan
dc.date.accessioned2023-12-26T18:43:16Z
dc.date.available2023-12-26T18:43:16Z
dc.date.issued2024-01-03
dc.identifier.doi10.24251/HICSS.2024.501
dc.identifier.isbn978-0-9981331-7-1
dc.identifier.other2e39dc10-6a50-4828-9eb9-ce2e67e61588
dc.identifier.urihttps://hdl.handle.net/10125/106885
dc.language.isoeng
dc.relation.ispartofProceedings of the 57th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectCrowd-based Platforms
dc.subjectfunctional data analysis
dc.subjectgroup differences
dc.subjectsocial media
dc.titleComparing Social Media Communities using Functional Data Analysis
dc.typeConference Paper
dc.type.dcmiText
dcterms.abstractVarious social media communities can lead conversations in entirely divergent directions, shaping the nature of information shared on these platforms. Deliberate disinformation and manipulated messages, disseminated both within and beyond these communities, hold the potential to reshape public opinion on a broader scale. A constructive analysis that delves into the disparities between these opposing groups could prove invaluable in discerning the pathways through which information flows. Our research examines the temporal dynamics of social media groups, assessing their behavior through metrics such as time dependent post and retweets. Using functional data analysis, we investigate Tweets related to incidents like the Skripal/Novichok case and the Bucha Crimes. Our goal is to quantify the disparities between these communities and uncover the strategies employed by each group to promote specific campaigns. Our preliminary findings shed new light on the mechanics of information dissemination, offering insights that may inform decisions about optimal response times.
dcterms.extent10 pages
prism.startingpage4162

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