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

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Title:Opinion Formation Threshold Estimates from Different Combinations of Social Media Data-Types
Authors:Asher, Derrik
Caylor, Justine
Doyle, Casey
Neigel, Alexis
Szymanski, Boleslaw
show 1 moreKorniss, Gyorgy
show less
Keywords:Social Media Management in Big Data Era
Digital and Social Media
experimental, human dynamics, MTurk, opinion spread, social media
Date Issued:08 Jan 2019
Abstract:Passive 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.
Pages/Duration:10 pages
URI:http://hdl.handle.net/10125/59706
ISBN:978-0-9981331-2-6
DOI:10.24251/HICSS.2019.324
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Social Media Management in Big Data Era


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