Mining personal media thresholds for opinion dynamics and social influence

To study the detailed effects of social media consumption on personal opinion dynamics, we gather self reported survey data on the volume of different media types an individual must consume before forming or changing their opinion on a subject. We then use frequent pattern mining to analyze the data...

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Bibliographic Details
Published in:Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining pp. 1258 - 1265
Main Authors: Doyle, Casey, Meandzija, Alex, Korniss, Gyorgy, Szymanski, Boleslaw, Asher, Derrik, Bowman, Elizabeth
Format: Conference Proceeding
Language:English
Published: Piscataway, NJ, USA IEEE Press 28.08.2018
Series:ACM Conferences
Subjects:
Information systems
Information systems > Information systems applications
Information systems > Information systems applications > Data mining
association rules
personal influence thresholds
crowdsourcing
social media
data mining
opinion formation
ISBN:1538660512, 9781538660515
Online Access:Get full text
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Summary:To study the detailed effects of social media consumption on personal opinion dynamics, we gather self reported survey data on the volume of different media types an individual must consume before forming or changing their opinion on a subject. We then use frequent pattern mining to analyze the data for common groupings of responses with respect to various media types, sources, and contexts. We show that in general individuals tend to perceive their behavior to be consistent across many variations in these parameters, while further detail shows various common parameter groupings that indicate response changes as well as small groups of individuals that tend to be consistently more easily swayed than the average participant.
ISBN:1538660512
9781538660515
DOI:10.5555/3382225.3382478