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Intuitively, personality traits may shape friendships differently from academic connections, potentially influencing social support development. Yet, this remains understudied, while it is crucial for student's wellbeing. Therefore, this study investigates how the personality traits of the Five-Factor Model interact with the role friendships and preferred collaboration relationships. In a sample of 95 university students, socio-centric data were collected with questionnaires on personality traits and longitudinally on networks of friendship and preferences for collaboration networks. Utilizing stochastic actor-oriented models in RSiena, we showed that students more open to new experiences established more friendships, preferred more collaborations with their peers, and were also more popular in both networks than students less open-to-new-experiences. Students scoring higher on agreeableness were less likely to connect to their peers in both networks, whereas higher-achieving students were more likely to establish peer relationships in both networks. Furthermore, friends were preferred for collaboration (and vice versa), indicating an overlap. This study points to the importance of personality traits and achievement when students integrate into their social and academic environment. [ABSTRACT FROM AUTHOR]

Community energy initiatives are set up by volunteers in local communities to promote sustainable energy behaviors and help to facilitate a sustainable energy transition. A key question is what motivates people to be involved in such initiatives. We propose that next to a stronger personal motivation for sustainable energy, people’s perception that their community is motivated to engage in sustainable energy and their involvement in the community (i.e., community identification and interpersonal contact) may affect their initiative involvement. We tested this proposition with a questionnaire study among inhabitants of seven local communities (N = 439). Results suggested that community factors are uniquely related to initiative involvement (willingness to actively participate and attendance of an initiative meeting) next to personal sustainable energy motivations. In particular, stronger community identification and more interpersonal contact with other community members increased the likelihood that people become involved in a community initiative, but the perception of the sustainable energy motivation of one’s community was not uniquely related to initiative involvement. We discuss theoretical and practical implications of these findings.

A common assumption about Freshmen Learning Communities (FLCs) is that academic relationships contribute to students' success. This study investigates how students in learning communities connect with fellow students for friendship and academic support. Longitudinal social network data across the first year, collected from 95 Dutch students in eight FLCs, measure both social and academic relational choices within and beyond the FLCs. Using stochastic actor-based models, the study tests two competing hypotheses. The alignment hypothesis states that students connect with their similar-achieving friends for both academic and social support, leading to an alignment of both types of networks over time. In contrast, the duality hypothesis states dissimilarity between academic support networks and friendship networks: students should connect with better-achieving fellow students for academic support and to more similar peers for friendship. The data support the alignment hypothesis but not the duality hypothesis; in addition, they show evidence of achievement segregation in FLCs: the higher the students' achievement level, the more they connect with other students for both academic support and friendship, relating in particular to peers with a similarly high achievement level. The results suggest that lower-achieving students are excluded from the support provided by higher-achieving students and instead ask similar lower achievers for support. They thus cannot benefit optimally from the academic integration FLC offer. The article concludes with recommendations of how to support students in an FLC so that they can reach optimal achievement potential.

Theoretical agent-based models of residential and school choice have shown that substantial segregation can emerge as an (unintended) consequence of interactions between individual households and feedback mechanisms, despite households being relatively tolerant. However, for school choice, existing models have mostly been highly stylized, leaving open whether they are relevant for understanding school segregation in concrete empirical settings. To bridge this gap, this study develops an empirically calibrated agent-based model focusing on primary school choice in Amsterdam. Consistent with existing models, results show that substantial school segregation emerges when schools are chosen based on a trade-off between composition and distance, and also when households are relatively tolerant. Additionally, findings of (hypothetical) policy simulations suggest that it is important to understand which preferences for school composition and distance households have and how these interact. We find that the effects of policies aiming to reduce school segregation through geographical restricting mechanisms are highly dependent on those interacting preferences. Also, we assessed the contribution of residential segregation to school segregation. Our findings may have implications for methodologies aiming to estimate school choice preferences, such as discrete choice models, as these methodologies do not explicitly control for implications of these interactions and feedback mechanisms, which might lead to incorrect inference. [ABSTRACT FROM AUTHOR]

Formal models of status construction theory suggest that beliefs about the relative social worth and competence of members of different social groups can emerge from face-to-face interactions in task-focused groups and eventually become consensual in large populations. We propose two extensions of earlier models. First, we incorporate the microlevel behavioral assumption of status construction theory that people can become resistant to belief change when a belief appears consensual in their local social environment. Second, we integrate the insight that the macro-level social structure of face-to-face interactions in large populations often is a clustered network structure. Computational experiments identify an outcome that was not anticipated by earlier formalizations. The combination of network clustering at the macrolevel and resistance to belief change at the microlevel can constrain the diffusion of status beliefs and generate regional variation in status beliefs. Further experiments identify conditions under which this outcome obtains.

Two theoretical approaches underlie this investigation of the determinants of early study success among first-year university students. Specifically, to extend Walberg's educational productivity model, this study draws on the expectancy-value theory of achievement motivation in a contemporary university context. The survey data came from 407 first-year students, and the measure of early study success reflects the weighted grade point average at two moments during their first semester. A path model reveals that the proposed extended educational productivity framework explains early study success well. The operationalised educational productivity factors (age, prior achievement, psychosocial environment, programme satisfaction, study skills) and achievement motivation (expectancy) all relate to early study success, directly or indirectly through expectancy and self-study. The two theoretical approaches jointly provide a thorough understanding of early study success. These results have notable implications for tracking students and for further research.

Identity diversity in teams brings advantages for complex decision-making because it is associated with cognitive diversity among team members. At the same time, homophilous interactions along shared identity dimensions can hinder information exchange among dissimilar individuals and threaten successful exploitation of the team’s cognitive diversity. We present an agent-based model to investigate how homophily impacts decision-making quality in diverse teams. Team members communicate information in a ‘hidden profile’ setting where some pieces of information are known only to single individuals while other pieces of information are known to subgroups with the same identity. While intuition may suggest that homophily impairs collective decision-making, our model reveals how homophilous environments lead to better collective decisions: homophily fosters temporary disagreements between dissimilar team members, which grant teams additional time to uncover crucial information that would not have been shared otherwise. Longer discussion time comes along with improvements in the quality of the final decision, indicating a trade-off between the time needed to deliberate and decision quality. [ABSTRACT FROM AUTHOR]

We formally introduce and empirically test alternative micro-foundations of social influence in the context of communication on social media. To this end, we first propose a general theoretical framework allowing us to represent by different combinations of model parameters of influence-response functions whether and to what extent exposure to online content leads to assimilative or repulsive (distancing) influence on a user’s opinion. We show by means of an agent-based model of opinion dynamics on social media that these influence-response functions indeed generate competing predictions about whether personalization (defined as the extent to which users are shielded from foreign opinions) increases or decreases polarization. Next, we conducted an online experiment with respondents recruited on Facebook to estimate model parameters empirically, using Bayesian models for censored data. In the experiment, participants´ opinions were measured before and after exposure to arguments reflecting different ideological positions and moral foundations in a within-subject design. Our findings support that exposure to foreign opinions leads to assimilation towards those opinions, moderated by the extent of (perceived) ideological similarity to the source of influence. We also find weak evidence in support of repulsion (distancing), but only for very large disagreement. Feeding estimated parameter values back into the agent-based model suggests that reducing personalization would not increase, but instead reduce the level of polarization generated by the opinion dynamics of the model. We conclude that the naive interpolation of micro-processes to macro-predictions can be misleading if models are not sufficiently empirically calibrated. [ABSTRACT FROM AUTHOR]

Formal models of opinion formation commonly represent an individual's opinion by a value on a fixed opinion interval. We propose an alternative modeling method wherein interpretation is only provided to the relative positions of opinions vis-à-vis each other. This method is then considered in a similar setting as the discrete-time Altafini model (an extension of the well-known DeGroot model), but with more general influence weights. Even in a linear framework, the model can describe, in the long run, polarization, dynamics with a periodic pattern, and (modulus) consensus formation. In addition, in our alternative approach key characteristics of the opinion dynamic can be derived from real-valued square matrices of influence weights, which immediately allows one to transfer matrix theory insights to the field of opinion formation dynamics under more relaxed conditions than in the DeGroot or discrete-time Altafini models. A few specific themes are covered: (i) We demonstrate how stable patterns in relative opinion dynamics are identified which are hidden when opinions are considered in an absolute opinion framework. (ii) For the two-agent case, we provide an exhaustive closed-form description of the relative opinion model's dynamic in the long run. (iii) We explore group dynamics analytically, in particular providing a non-trivial condition under which a subgroup's asymptotic behavior carries over to the entire population. [ABSTRACT FROM AUTHOR]

Since the first publication of the bounded-confidence models 20 years ago, hundreds of articles studying this class of social-influence models have been written. Bounded-confidence models proposed an intriguing solution to a pervasive research puzzle and have helped unveil and explain intriguing phenomena. Here, we reflect about remaining research problems and future modeling challenges, arguing that there remain counter-intuitive model implications to be understood. To illustrate that there remain uncovered model challenges, we extend the bounded-confidence model. We assume assimilative influence when agents connected by positive relationships hold sufficiently similar opinions, adopting the core assumption of the bounded-confidence models. We combine this with another influential modeling approach, the notion that if agents connected by a negative social relationship disagree too much, opinion differences increase due to repulsive influence. This allows us to vary the relative strength of assimilation and repulsion in the influence dynamics, also allowing for the possibility that neither occurs in a particular interaction. Simulation experiments reveal three surprising findings: Counter the intuition that stronger assimilation decreases opinion diversity, we show that in the presence of repulsion, intensifying the strength of assimilation can actually generate more opinion bipolarization. Second, we show that if repulsion becomes weaker this may still result in more bipolarization. Third, it turns out that more negative social relationships between or within subgroups can result in less bipolarization. We demonstrate these effects in very simple and highly stylized settings, in order to show that intuition fails to capture the complexity arising from the interplay of assimilative and repulsive influence even in these simple settings. We discuss implications of our findings for the ongoing debate about societal conditions fostering bipolarization, including in particular the design of personalized online social networks. Further, we address how our results may inform future work comparing and integrating alternative models of social-influence dynamics. [ABSTRACT FROM AUTHOR]

How can we reduce ethnic friendship segregation in ethnically heterogeneous schools? The Common Ingroup Identity Model suggests that interethnic friendships are promoted by those intervention programs that focus on the interests students have in common. The authors argue that the outcome of these common interest interventions may crucially depend on sufficient consensus in participants' opinions regarding the shared interest. Such an intervention may backfire and increase ethnic segregation if participants from different ethnic groups have different opinions about the common interest. The authors test their argument analyzing the dynamics of friendship networks and opinions in 48 school classes with an actor-based stochastic model. Their findings suggest that salient common interests in ethnically mixed school classes can indeed reduce ethnic segregation. However, they also found that friendship selection on the basis of similar opinions can foster ethnic segregation. This occurred when ethnicity was correlated with the opinions that students held regarding the salient interest, even when these students did not prefer intra-ethnic friendship per se. (Contains 1 figure, 6 tables and 5 notes.)