A paper titled "Opinion Formation Threshold Estimates from Different Combinations of Social Media Data-Types," co-authored by Casey Doyle, G. Korniss, and Boleslaw K. Szymanski of NEST was published in Proc. HICSS 2019.

A paper titled "Opinion Formation Threshold Estimates from Different Combinations of Social Media Data-Types," co-authored by Derrik E. Asher, Justine Caylor, Casey Doyle, Alexis R. Neigel, G. Korniss, and Boleslaw K. Szymanski was published in Proc. 52nd Hawaii International Conference on System Sciences (HICSS 2019), Grand Wailea, HI, Jan 8-11, 2019. The paper studies what amount of passive consumption 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. The paper is available at the link below.