scholarly journals The Strength of Weak Leaders An Experiment on Social Influence and Social Learning in Teams

2017 ◽  
Author(s):  
Berno Buechel ◽  
Stefan Klllner ◽  
Martin Lochmmller ◽  
Heiko Rauhut
Keyword(s):  
Social Learning ◽  
Social Influence

scholarly journals The computational basis of following advice in adolescents

2018 ◽  
Author(s):  
Julia Rodriguez ◽  
Hauke Heekeren ◽  
Wouter van den Bos
Keyword(s):  
Social Learning ◽  
Comparative Study ◽  
Social Influence ◽  
Peer Influence ◽  
Dynamic Interaction ◽  
Individual Learning ◽  
Developmental Differences ◽  
The Other ◽  
Current Task ◽  
Computational Basis

Advice taking helps one quickly acquire knowledge and make decisions. This age-comparative study (in 8-10, 13-15 and 18-22 year olds) investigated developmental differences in how advice, experience and exploration influence learning. The results showed that adolescents were initially easily swayed to follow peer advice but also switched more rapidly to exploring alternatives, like children. Whereas adults stayed with the advice over the task, adolescents put more weight on their own experience compared to adults. A social learning model showed that although social influence most strongly impacts adolescents’ initial expectations (i.e., their priors), they showed higher exploration and discovered the other good option in the current task. Thus, our model resolved the apparently conflicting findings of adolescents being more and less sensitive to peer influence and provides novel insights in the dynamic interaction between social and individual learning.

scholarly journals Social Influence in Prosocial Behavior: Evidence from a Large-Scale Experiment

2020 ◽  
Author(s):  
Lorenz Goette ◽  
Egon Tripodi
Keyword(s):  
Social Learning ◽  
Social Influence ◽  
Prosocial Behavior ◽  
Large Scale ◽  
Crowding Out ◽  
The Social ◽  
Social Reference ◽  
Scale Experiment ◽  
Underlying Mechanisms

Abstract We propose a novel experiment that prevents social learning, thus allowing us to disentangle the underlying mechanisms of social influence. Subjects observe their peer’s incentives, but not their behavior. We find evidence of conformity: when individuals believe that incentives make others contribute more, they also increase their contributions. Conformity is driven by individuals who feel socially close to their peer. However, when incentives are not expected to raise their peer’s contributions, participants reduce their own contributions. Our data is consistent with an erosion of norm-adherence when prosocial behavior of the social reference is driven by extrinsic motives, and cannot be explained by incentive inequality or altruistic crowding out. These findings show scope for social influence in settings with limited observability and offer insights into the mediators of conformity.

Understanding social networks requires more than two dimensions

2014 ◽  
Vol 37 (1) ◽  
pp. 99-99
Author(s):  
Derek Ruths ◽  
Thomas Shultz
Keyword(s):  
Decision Making ◽  
Social Networks ◽  
Social Learning ◽  
Social Influence ◽  
Two Dimensions ◽  
Current Evidence ◽  
Learning Techniques

AbstractThe proposed framework is insufficient to categorize and understand current evidence on decision making. There are some ambiguities in the questions asked that require additional distinctions between correctness and accuracy, decision making and learning, accuracy and confidence, and social influence and empowerment. Social learning techniques are not all the same: Behavior copying is quite different from theory passing. Sigmoidal acquisition curves are not unique to social learning and are often mistaken for other accelerating curves.

Wary learners

2019 ◽  
pp. 21-48
Author(s):  
Alberto Acerbi
Keyword(s):  
Social Learning ◽  
Social Influence ◽  
Learning Strategies ◽  
Interdisciplinary Approach ◽  
Point Of View ◽  
Human Cognition ◽  
Cognitive Mechanisms ◽  
Cognitive Operations ◽  
The Individual ◽  
Social Learning Strategies

Cultural evolution is a diverse field of research, but some similarities can be found: cultural evolutionists defend a quantitative, naturalistic, and interdisciplinary approach to the study of human culture. Importantly, cultural evolutionists are committed to develop sound hypotheses about the individual psychology that drives our cultural behavior. Although there are different nuances, a common idea is that human cognition is specialized for processing social interactions, communication, and learning from others. From an evolutionary point of view, the cognitive mechanisms involved should produce, on average, adaptive outcomes. From this perspective, social learning strategies (a series of relatively simple, general-domain, heuristics to choose when, what, and from whom to copy) provide a first boundary to indiscriminate social influence. I critically examine the concept of social learning strategies, and I discuss how cultural evolutionists may have overestimated both the effect of social influence and, possibly, our reliance of social learning itself. I also discuss the perspective from epistemic vigilance theory, which gives more weight to the possibility of explicit deception, and proposes that we apply sophisticated cognitive operations when deciding whether to trust information coming from others.

scholarly journals The Strength of Weak Leaders - An Experiment on Social Influence and Social Learning in Teams

2018 ◽  
Author(s):  
Berno Buechel ◽  
Stefan Klllner ◽  
Martin Lochmmller ◽  
Heiko Rauhut
Keyword(s):  
Social Learning ◽  
Social Influence

scholarly journals The strength of weak leaders: an experiment on social influence and social learning in teams

2019 ◽  
Vol 23 (2) ◽  
pp. 259-293
Author(s):  
Berno Buechel ◽  
Stefan Klößner ◽  
Martin Lochmüller ◽  
Heiko Rauhut
Keyword(s):  
Social Learning ◽  
Social Influence

Understanding relational virtual community members’ satisfaction from a social learning perspective

2020 ◽  
Vol 24 (6) ◽  
pp. 1425-1443
Author(s):  
Shih-Wei Chou
Keyword(s):  
Social Learning ◽  
Social Influence ◽  
Goal Orientation ◽  
Cognitive Theory ◽  
Virtual Community ◽  
Two Dimensions ◽  
Community Members ◽  
Content Type ◽  
Learning Goal ◽  
Learning Goal Orientation

Purpose This study develops a belief-value-satisfaction model based on social cognitive theory. This paper aims to explain how relational virtual community (RVC) members’ beliefs on individual features and environments can be transformed into satisfaction through social learning strategies. Design/methodology/approach The authors followed a longitudinal, quasi-experimental field approach to collect data from two phases, which entailed the key informant approach to get the responses from those who participated in knowledge exchange in VC. The authors used partial least squares to examine the proposed hypotheses. Findings Satisfaction is measured as two dimensions – outcome and process. Value creation is conceptualized as social self-regulated learning (SRL), and its antecedents include lead userness, learning goal orientation and social influence. The results show that both dimensions of satisfaction are affected by social SRL, which in turn is influenced by learning goal orientation and social influence. Originality/value A systematic research for understanding satisfaction from a social learning perspective in relational virtual community settings remains absent. This study explains why and how relational virtual community members’ social SRL serves the role in leveraging resources and reducing uncertainty, from which they gain satisfaction.

scholarly journals Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence, and Social Learning

2009 ◽  
Vol 99 (5) ◽  
pp. 1899-1924 ◽  
Author(s):  
H. Peyton Young
Keyword(s):  
Social Learning ◽  
Social Influence ◽  
Innovation Diffusion ◽  
Diffusion Models ◽  
Hybrid Corn ◽  
Heterogeneous Populations ◽  
New Ideas ◽  
High Level

New ideas, products, and practices take time to diffuse, a fact that is often attributed to some form of heterogeneity among potential adopters. This paper examines three broad classes of diffusion models—contagion, social influence, and social learning—and shows how to incorporate heterogeneity into each at a high level of generality without losing analytical tractability. Each type of model leaves a characteristic “footprint” on the shape of the adoption curve which provides a basis for discriminating empirically between them. The approach is illustrated using the classic study of Ryan and Gross (1943) on the diffusion of hybrid corn. (JEL D83, O33, Q16, Z13)

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