Discrepancy and Disliking Do Not Induce Negative Opinion Shifts

Abstract

Both classical social psychological theories and recent formal models of opinion differentiation and bi-polarization assign a prominent role to negative social influence. Negative influence is defined as shifts away from the opinion of others and hypothesized to be induced by discrepancy with or disliking of the source of influence. There is strong empirical support for the presence of positive social influence (a shift towards the opinion of others), but evidence that large opinion differences or disliking could trigger negative shifts is mixed. We examine positive and negative influence with controlled exposure to opinions of other individuals in one experiment and with opinion exchange in another study. Results confirm that similarities induce attraction, but results do not support that discrepancy or disliking entails negative influence. Instead, our findings suggest a robust positive linear relationship between opinion distance and opinion shifts.

Towards representing human behavior and decision making in Earth system models – an overview of techniques and approaches

“…Classical models incorporate influence as averaging, which implies that interacting individuals always grow more similar over time (Friedkin and Johnsen, 2011). Averaging is an accepted and empirically supported model of influence resulting, for instance, from the social pressure that an actor exerts on someone else (Takács et al, 2016). Models assume different forms of averaging.…”

Cognitive perspectives on opinion dynamics: the role of knowledge in consensus formation, opinion divergence, and group polarization

“…Also relevant to this is recent empirical research has begun to emerge attempting to test assumptions of opinion dynamics models-looking at the conditions under which humans are willing to change their opinion or an estimate, as a function of both the size of the difference and their confidence in their knowledge [34,49,50]. Contrary to the assumptions of bounded influence, Moussaid and colleagues [34] found that when opinion differences are small, this typically resulted in no change; as they grew larger, a change (either a compromise estimate or adoption of the others's value) became relatively more likely, although the chance of adopting another's estimate wholesale (in contrast to a compromise value) went down as the opinion difference got very large.…”

“…To be fair, this last finding is consistent with the bounded influence conjecture, but may also be consistent with other accounts. Similarly, Kerckhove [49] measured how easily participants were influenced by group judgments, and found that those who differed the most from the group judgment were most influenced, and Takacs [50] similarly showed that larger differences of opinion lead to larger overall changes.…”

Opinion evolution in time-varying social influence networks with prejudiced agents

“…Similar to continuous-time clustering protocols with "informed" leaders (Xia and Cao, 2011), the heterogeneity of the prejudices and its linkage to individuals' susceptibilities to interpersonal influence may lead to persistent disagreement of opinions and outcomes such as polarization and clustering. With the FJ model, the clustering of opinions does not require the existence of repulsive couplings, or "negative ties" among individuals (Fläche and Macy, 2011;Altafini, 2013;Proskurnikov et al, 2016a;Xia et al, 2016) whose ubiquity in interpersonal interactions is still waiting for supporting experimental evidence (Takács et al, 2016). Unlike models with discrete opinions (Castellano et al, 2009) and bounded confidence models (Hegselmann and Krause, 2002;Weisbuch et al, 2005;Blondel et al, 2009), the FJ model describes the opinion evolution by linear discrete-time equations, and is thus much simpler for mathematical analysis.…”