In this paper, we present an empirical study of the opinion dynamics of a large-scale sample of online social network users. Opinions of users are estimated based on their subscriptions to information sources and we analyze how friendship connections affect the dynamics of these estimations. Our analysis has revealed traces of both positive (assimilative ) and negative ( repulsive) influence in how users decide whether to change their opinions , while magnitudes of changed opinions appear to obey a positive influence. We also found that individuals with networks that include many ideologically opposite users are less prone to radicalization than those with homogenous ones. Our results indicate that the opinion dynamics of online social network users cannot be described solely by any concrete theoretical opinion formation model; rather, they include patterns of multiple models simultaneously .
In this paper, we present an empirical study of the opinion dynamics of a large-scale sample of online social network users. We estimate opinions of users as continuous scalars based on their subscriptions to information sources and analyze how friendship connections affect the dynamics of these estimations. Distinguishing between positive (toward opinions of friends ) and negative ( away from opinions of friends) opinion shifts, we find that the existence and magnitude of opinion shifts are positively related (largely through a linear form or an inverted U-shaped form) to the degree of divergence in opinions between user and their friends. Additionally, we moderate the balance between positive and negative shifts using opinion divergence: if the opinions of the focal user and their friends are too similar or dissimilar, there is a relatively low chance of a positive shift .
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Opinions of users are estimated
We estimate opinions of users as continuous scalars
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we
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Our analysis has revealed traces of both positive (assimilative
Distinguishing between positive (toward opinions of friends
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repulsive) influence in how users decide whether to change their opinions , while magnitudes of changed opinions appear to obey a positive influence. We also found that individuals with networks that include many ideologically opposite users are less prone to radicalization than those with homogenous ones. Our results indicate that the opinion dynamics of online social network users cannot be described solely by any concrete theoretical opinion formation model; rather, they include patterns of multiple models simultaneously
away from opinions of friends) opinion shifts, we find that the existence and magnitude of opinion shifts are positively related (largely through a linear form or an inverted U-shaped form) to the degree of divergence in opinions between user and their friends. Additionally, we moderate the balance between positive and negative shifts using opinion divergence: if the opinions of the focal user and their friends are too similar or dissimilar, there is a relatively low chance of a positive shift