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

TL;DR

This study investigates how different types and contexts of social media data influence opinion formation thresholds in individuals, providing a theoretical framework for understanding data-driven opinion shifts in society.

Contribution

It introduces a method to estimate opinion formation thresholds based on social media data types, contexts, and sources, supported by empirical data from 2222 participants.

Findings

Different data types have varying influence on opinion formation.

Context and source significantly affect the threshold levels.

Provides a theoretical model for data-driven opinion influence.

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, and 3) source. This work provides a theoretical basis for estimating the amount of data needed to influence a population through social media information.