Michael Mäs
University of Groningen
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by Michael Mäs.
PLOS Computational Biology | 2010
Michael Mäs; Andreas Flache; Dirk Helbing
One of the most intriguing dynamics in biological systems is the emergence of clustering, in the sense that individuals self-organize into separate agglomerations in physical or behavioral space. Several theories have been developed to explain clustering in, for instance, multi-cellular organisms, ant colonies, bee hives, flocks of birds, schools of fish, and animal herds. A persistent puzzle, however, is the clustering of opinions in human populations, particularly when opinions vary continuously, such as the degree to which citizens are in favor of or against a vaccination program. Existing continuous opinion formation models predict “monoculture” in the long run, unless subsets of the population are perfectly separated from each other. Yet, social diversity is a robust empirical phenomenon, although perfect separation is hardly possible in an increasingly connected world. Considering randomness has not overcome the theoretical shortcomings so far. Small perturbations of individual opinions trigger social influence cascades that inevitably lead to monoculture, while larger noise disrupts opinion clusters and results in rampant individualism without any social structure. Our solution to the puzzle builds on recent empirical research, combining the integrative tendencies of social influence with the disintegrative effects of individualization. A key element of the new computational model is an adaptive kind of noise. We conduct computer simulation experiments demonstrating that with this kind of noise a third phase besides individualism and monoculture becomes possible, characterized by the formation of metastable clusters with diversity between and consensus within clusters. When clusters are small, individualization tendencies are too weak to prohibit a fusion of clusters. When clusters grow too large, however, individualization increases in strength, which promotes their splitting. In summary, the new model can explain cultural clustering in human societies. Strikingly, model predictions are not only robust to “noise”—randomness is actually the central mechanism that sustains pluralism and clustering.
Computational and Mathematical Organization Theory | 2008
Andreas Flache; Michael Mäs
Lau and Murnighan’s faultline theory explains negative effects of demographic diversity on team performance as consequence of strong demographic faultlines. If demographic differences between group members are correlated across various dimensions, the team is likely to show a “subgroup split” that inhibits communication and effective collaboration between team members. Our paper proposes a rigorous formal and computational reconstruction of the theory. Our model integrates four elementary mechanisms of social interaction, homophily, heterophobia, social influence and rejection into a computational representation of the dynamics of both opinions and social relations in the team. Computational experiments demonstrate that the central claims of faultline theory are consistent with the model. We show furthermore that the model highlights a new structural condition that may give managers a handle to temper the negative effects of strong demographic faultlines. We call this condition the timing of contacts. Computational analyses reveal that negative effects of strong faultlines critically depend on who is when brought in contact with whom in the process of social interactions in the team. More specifically, we demonstrate that faultlines have hardly negative effects when teams are initially split into demographically homogeneous subteams that are merged only when a local consensus has developed.
PLOS ONE | 2013
Michael Mäs; Andreas Flache
Explanations of opinion bi-polarization hinge on the assumption of negative influence, individuals’ striving to amplify differences to disliked others. However, empirical evidence for negative influence is inconclusive, which motivated us to search for an alternative explanation. Here, we demonstrate that bi-polarization can be explained without negative influence, drawing on theories that emphasize the communication of arguments as central mechanism of influence. Due to homophily, actors interact mainly with others whose arguments will intensify existing tendencies for or against the issue at stake. We develop an agent-based model of this theory and compare its implications to those of existing social-influence models, deriving testable hypotheses about the conditions of bi-polarization. Hypotheses were tested with a group-discussion experiment (N = 96). Results demonstrate that argument exchange can entail bi-polarization even when there is no negative influence.
Simulation Modelling Practice and Theory | 2008
Andreas Flache; Michael Mäs
Abstract Lau and Murnighan (LM) suggested that strong demographic faultlines threaten team cohesion and reduce consensus. However, it remains unclear which assumptions are exactly needed to derive faultline effects. We propose a formal computational model of the effects of faultlines that uses four elementary social mechanisms, social influence, rejection, homophily and heterophobia. We show that our model is consistent with the central hypotheses of LM’s theory. We also find that negative effects of faultlines can be derived even when – unlike LM – we assume that initially there is no correlation between the demographic characteristics and the opinions of team members.
Journal of Economic Theory | 2016
Michael Mäs; Heinrich H. Nax
‘Noise’ in this study, in the sense of evolutionary game theory, refers to deviations from prevailing behavioral rules. Analyzing data from a laboratory experiment on coordination in networks, we tested ‘what kind of noise’ is supported by behavioral evidence. This empirical analysis complements a growing theoretical literature on ‘how noise matters’ for equilibrium selection. We find that the vast majority of decisions (96%96%) constitute myopic best responses, but deviations continue to occur with probabilities that are sensitive to their costs, that is, less frequent when implying larger payoff losses relative to the myopic best response. In addition, deviation rates vary with patterns of realized payoffs that are related to trial-and-error behavior. While there is little evidence that deviations are clustered in time or space, there is evidence of individual heterogeneity.
Springer US | 2014
Michael Mäs; Andreas Flache; James A. Kitts
Experimental and field research has demonstrated a pervasive tendency toward pairwise conformity among individuals connected by positive social ties, and work using formal models has shown that opinions on connected influence networks should thus converge toward uniformity. Observing that diversity persists even in small scale groups and organizations, we investigate two empirically grounded mechanisms of social differentiation that may account for this persistence: First, actors may dislike or disrespect peers who diverge too much from their own views, and may change their opinions or behaviors to distance themselves further from those negative referents. Second, when surrounded by similar others, actors may try to maintain a sufficient sense of uniqueness by exploring new opinions or behaviors. Using computational experiments, we demonstrate that these two mechanisms lead to different patterns of polarization, radicalization, and factionalism and also investigate the conditions under which integration occurs. In closing, we discuss the implications for cultural dynamics in organizations.
PLOS ONE | 2016
Károly Takács; Andreas Flache; Michael Mäs
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.
PLOS ONE | 2015
Stefano Balietti; Michael Mäs; Dirk Helbing
Why are some scientific disciplines, such as sociology and psychology, more fragmented into conflicting schools of thought than other fields, such as physics and biology? Furthermore, why does high fragmentation tend to coincide with limited scientific progress? We analyzed a formal model where scientists seek to identify the correct answer to a research question. Each scientist is influenced by three forces: (i) signals received from the correct answer to the question; (ii) peer influence; and (iii) noise. We observed the emergence of different macroscopic patterns of collective exploration, and studied how the three forces affect the degree to which disciplines fall apart into divergent fragments, or so-called “schools of thought”. We conducted two simulation experiments where we tested (A) whether the three forces foster or hamper progress, and (B) whether disciplinary fragmentation causally affects scientific progress and vice versa. We found that fragmentation critically limits scientific progress. Strikingly, there is no effect in the opposite causal direction. What is more, our results shows that at the heart of the mechanisms driving scientific progress we find (i) social interactions, and (ii) peer disagreement. In fact, fragmentation is increased and progress limited if the simulated scientists are open to influence only by peers with very similar views, or when within-school diversity is lost. Finally, disciplines where the scientists received strong signals from the correct answer were less fragmented and experienced faster progress. We discuss model’s implications for the design of social institutions fostering interdisciplinarity and participation in science.
PLOS ONE | 2014
Michael Mäs; Jacob Dijkstra
We developed a new experimental design to test whether or not individuals engage in conflict between social groups because they seek to harm outgroup members. Challenging prominent social psychological theories, we did not find support for such negative social preferences. Nevertheless, subjects heavily engaged in group conflict. Results support the argument that processes that act within social groups motivate engagement in conflict between groups even in the absence of negative social preferences. In particular, we found that “cheap talk” communication between group members fuels conflict. Analyses did not support the notion that the effect of communication results from guilt-aversion processes.
Social Networks | 2016
Michael Mäs; Karl-Dieter Opp
Abstract It has been hypothesized that disclosing a populations true rate of norm violation increases norm-violating behavior. Withholding such information might, thus, prevent the attenuation of useful norms. Analyzing a classical threshold model with flexible thresholds, we show that disclosing the true rate of norm violation can spark cascades of norm violation but can also have the opposite effect, decreasing norm violation and strengthening norm acceptance. The direction of the cascade depends on the initial rate of norm violation. Furthermore, the disclosure effect depends on whether or not the rate of norm violation is disclosed repeatedly, the structure of the social network, and whether individuals’ norm acceptance is inelastic or open to peer-influence.