Opinion Formation Threshold Estimates from Different Combinations of Social Media Data-Types

dc.contributor.authorAsher, Derrik
dc.contributor.authorCaylor, Justine
dc.contributor.authorDoyle, Casey
dc.contributor.authorNeigel, Alexis
dc.contributor.authorSzymanski, Boleslaw
dc.contributor.authorKorniss, Gyorgy
dc.date.accessioned2019-01-03T00:07:06Z
dc.date.available2019-01-03T00:07:06Z
dc.date.issued2019-01-08
dc.description.abstractPassive consumption of a quantifiable amount of social media information related to a topic can cause individuals to form opinions. If a substantial amount of these individuals are motivated to take action from their recently established opinions, a movement or public opinion shift can be induced independent of the information’s veracity. Given that social media is ubiquitous in modern society, it is imperative that we understand the threshold at which social media data results in opinion formation. The present study estimates population opinion formation thresholds by querying 2222 participants about the number of various social media data-types (i.e., images, videos, and/or messages) that they would need to passively consume to form opinions. Opinion formation is assessed across three dimensions, 1) data-type(s), 2) context, 3) and source. This work provides a theoretical basis for estimating the amount of data needed to influence a population through social media information.
dc.format.extent10 pages
dc.identifier.doihttps://doi.org/10.24251/HICSS.2019.324
dc.identifier.isbn978-0-9981331-2-6
dc.identifier.urihttp://hdl.handle.net/10125/59706
dc.language.isoeng
dc.relation.ispartofProceedings of the 52nd 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.subjectSocial Media Management in Big Data Era
dc.subjectDigital and Social Media
dc.subjectexperimental, human dynamics, MTurk, opinion spread, social media
dc.titleOpinion Formation Threshold Estimates from Different Combinations of Social Media Data-Types
dc.typeConference Paper
dc.type.dcmiText

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