Journal articles: 'Stochastic-actor oriented model'

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Lospinoso, Josh, and Tom AB Snijders. "Goodness of fit for stochastic actor-oriented models." Methodological Innovations 12, no. 3 (September 2019): 205979911988428. http://dx.doi.org/10.1177/2059799119884282.

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We propose a Mahalanobis distance–based Monte Carlo goodness of fit testing procedure for the family of stochastic actor-oriented models for social network evolution. A modified model distance estimator is proposed to help the researcher identify model extensions that will remediate poor fit. A limited simulation study is provided to establish baseline legitimacy for the Mahalanobis distance–based Monte Carlo test and modified model distance estimator. A forward model selection workflow is proposed, and this procedure is demonstrated on a real data set.

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INDLEKOFER, NATALIE, and ULRIK BRANDES. "Relative importance of effects in stochastic actor-oriented models." Network Science 1, no. 3 (December 2013): 278–304. http://dx.doi.org/10.1017/nws.2013.21.

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AbstractA measure of relative importance of network effects in the stochastic actor-oriented model (SAOM) is proposed. The SAOM is a parametric model for statistical inference in longitudinal social networks. The complexity of the model makes the interpretation of inferred results difficult. So far, the focus is on significance tests while the relative importance of effects is usually ignored. Indeed, there is no established measure to determine the relative importance of an effect in a SAOM. We introduce such a measure based on the influence effects have on decisions of individual actors in the network. We demonstrate its utility on empirical data by analyzing an evolving friendship network of university freshmen.

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Niezink, Nynke M. D., Tom A. B. Snijders, and Marijtje A. J. van Duijn. "No Longer Discrete: Modeling the Dynamics of Social Networks and Continuous Behavior." Sociological Methodology 49, no. 1 (May 9, 2019): 295–340. http://dx.doi.org/10.1177/0081175019842263.

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The dynamics of individual behavior are related to the dynamics of the social structures in which individuals are embedded. This implies that in order to study social mechanisms such as social selection or peer influence, we need to model the evolution of social networks and the attributes of network actors as interdependent processes. The stochastic actor-oriented model is a statistical approach to study network-attribute coevolution based on longitudinal data. In its standard specification, the coevolving actor attributes are assumed to be measured on an ordinal categorical scale. Continuous variables first need to be discretized to fit into such a modeling framework. This article presents an extension of the stochastic actor-oriented model that does away with this restriction by using a stochastic differential equation to model the evolution of a continuous attribute. We propose a measure for explained variance and give an interpretation of parameter sizes. The proposed method is illustrated by a study of the relationship between friendship, alcohol consumption, and self-esteem among adolescents.

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Kalish, Yuval. "Stochastic Actor-Oriented Models for the Co-Evolution of Networks and Behavior: An Introduction and Tutorial." Organizational Research Methods 23, no. 3 (January 23, 2019): 511–34. http://dx.doi.org/10.1177/1094428118825300.

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Stochastic actor-oriented (SAO) models are a family of models for network dynamics that enable researchers to test multiple, often competing explanations for network change and estimate the extent and relative power of various influences on network evolution. SAO models for the co-evolution of network ties and actor behavior, the most comprehensive category of SAO models, examine how networks and actor attributes—their behavior, performance, or attitudes—influence each other over time. While these models have been widely used in the social sciences, and particularly in educational settings, their use in organizational scholarship has been extremely limited. This paper provides a layperson introduction to SAO models for the co-evolution of networks and behavior and the types of research questions they can address. The models and their underpinnings are explained in nonmathematical terms, and theoretical explanations are supported by a concrete, detailed example that includes step-by-step model building and hypothesis testing, alongside an R script.

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Westra, Daan, Federica Angeli, Martin Carree, and Dirk Ruwaard. "Does Price Competition Drive Cooperation in Health Care? A Stochastic Actor Oriented Model Analysis." Academy of Management Proceedings 2016, no. 1 (January 2016): 12839. http://dx.doi.org/10.5465/ambpp.2016.12839abstract.

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Leifeld, Philip, and Skyler J. Cranmer. "A theoretical and empirical comparison of the temporal exponential random graph model and the stochastic actor-oriented model." Network Science 7, no. 1 (March 2019): 20–51. http://dx.doi.org/10.1017/nws.2018.26.

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AbstractThe temporal exponential random graph model (TERGM) and the stochastic actor-oriented model (SAOM, e.g., SIENA) are popular models for longitudinal network analysis. We compare these models theoretically, via simulation, and through a real-data example in order to assess their relative strengths and weaknesses. Though we do not aim to make a general claim about either being superior to the other across all specifications, we highlight several theoretical differences the analyst might consider and find that with some specifications, the two models behave very similarly, while each model out-predicts the other one the more the specific assumptions of the respective model are met.

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Leifeld, Philip, and Skyler J. Cranmer. "A theoretical and empirical comparison of the temporal exponential random graph model and the stochastic actor-oriented model – Corrigendum." Network Science 10, no. 1 (March 2022): 111. http://dx.doi.org/10.1017/nws.2022.11.

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Block, Per, Christoph Stadtfeld, and Tom A. B. Snijders. "Forms of Dependence: Comparing SAOMs and ERGMs From Basic Principles." Sociological Methods & Research 48, no. 1 (November 17, 2016): 202–39. http://dx.doi.org/10.1177/0049124116672680.

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Two approaches for the statistical analysis of social network generation are widely used; the tie-oriented exponential random graph model (ERGM) and the stochastic actor-oriented model (SAOM) or Siena model. While the choice for either model by empirical researchers often seems arbitrary, there are important differences between these models that current literature tends to miss. First, the ERGM is defined on the graph level, while the SAOM is defined on the transition level. This allows the SAOM to model asymmetric or one-sided tie transition dependence. Second, network statistics in the ERGM are defined globally but are nested in actors in the SAOM. Consequently, dependence assumptions in the SAOM are generally stronger than in the ERGM. Resulting from both, meso- and macro-level properties of networks that can be represented by either model differ substantively and analyzing the same network employing ERGMs and SAOMs can lead to distinct results. Guidelines for theoretically founded model choice are suggested.

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Kang, Ahrom, Joongsan Oh, and Chulsoon Park. "Evolution of the Korean Automotive Industry Supply Network: An Exploratory Study Based on SAOM (Stochastic Actor-Oriented Model)*." Korean Production and Operations Management Society 33, no. 4 (December 30, 2022): 699–721. http://dx.doi.org/10.32956/kopoms.2022.33.4.699.

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Most studies on the supply network structure have focused on revealing the “stationary’ network structure based on cross-sectional data. However, when the supply network is defined as a complex adaptive system that is a dynamic process, it is particularly important to explore its structure and evolution. Therefore, this study empirically analyzed how and through which micro-mechanisms the traditional vertical structure of the Korean automotive industry supply network is evolving into a horizontal structure. The results confirmed that new firms were continuously entering the Korean automotive industry supply network, and transaction relationships that were not found in the traditional supply chain structure were increasing. Additionally, among the existing suppliers, high-performing suppliers continued to form new transaction relationships while maintaining existing relationships. The significance of this study is as follows. SAOM was applied to the supply network of the Korean automotive industry for the first time, and the existing vertical and linear relationship studies were expanded from a network perspective. Furthermore, unlike the existing supply network-related studies, which were limited to an analysis at a specific point in time, the dynamic evolution of the supply network was identified.

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Xing, Lizhi, and Wen Chen. "Structural Characteristics and Evolutionary Drivers of Global Virtual Water Trade Networks: A Stochastic Actor-Oriented Model for 2000–2015." International Journal of Environmental Research and Public Health 20, no. 4 (February 12, 2023): 3234. http://dx.doi.org/10.3390/ijerph20043234.

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The globalization of trade has caused tremendous pressure on water resources globally, and a virtual water trade provides a new perspective on global freshwater sharing and water sustainability. No study has yet explored the structural characteristics and drivers of the evolution of global virtual water trade networks from a network structure evolution perspective. This paper aims to fill this critical gap by developing a research framework to explore how endogenous network structures and external factors have influenced the evolution of virtual water trade networks. We constructed virtual water trade networks for 62 countries worldwide from 2000 to 2015 and used an innovative combination of multi-regional input–output data and stochastic actor-oriented models for analytical purposes. Our results support the theoretical hypothesis of ecologically unequal exchange and trade drivers, arguing that virtual water flows from less developed countries to developed countries under global free trade and that unequal trade patterns lead to excessive consumption of virtual water in less developed countries. The results partially support the theoretical content of water endowment and traditional gravity models, finding that trade networks are expanding to farther and larger markets, confirming that national water scarcity levels do not impact the evolution of virtual water trade networks. Finally, we point out that meritocratic links, path dependence, reciprocity, and transmissive links have extreme explanatory power for the evolutionary development of virtual water networks.

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Snijders, Tom A. B., and Alessandro Lomi. "Beyond homophily: Incorporating actor variables in statistical network models." Network Science 7, no. 1 (March 2019): 1–19. http://dx.doi.org/10.1017/nws.2018.30.

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AbstractWe consider the specification of effects of numerical actor attributes, having an interval level of measurement, in statistical models for directed social networks. A fundamental mechanism is homophily or assortativity, where actors have a higher likelihood to be tied with others having similar values of the variable under study. But there are other mechanisms that may also play a role in how the attribute values of two actors influence the likelihood of a tie between them. We discuss three additional mechanisms: aspiration, the tendency to send more ties to others having high values; attachment conformity, sending more ties to others whose values are close to the “social norm”; and sociability, where those having higher values will tend to send more ties generally. These mechanisms may operate jointly, and then their effects will be confounded. We present a specification representing these effects simultaneously by a four-parameter quadratic function of the values of sender and receiver. Flexibility can be increased by a five-parameter extension. We argue that for numerical actor attributes having important effects on directed networks, these specifications may provide an improvement. An illustration is given of dependence of advice ties on academic grades, analyzed by the Stochastic Actor-oriented Model.

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Sadewo, Giovanni R. P., Emiko S. Kashima, Colin Gallagher, Yoshihisa Kashima, and Johan Koskinen. "International Students’ Cross-Cultural Adjustment: Social Selection or Social Influence?" Journal of Cross-Cultural Psychology 51, no. 6 (June 8, 2020): 490–510. http://dx.doi.org/10.1177/0022022120930092.

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International education provides students with an opportunity to develop new social networks while they fit in to the new culture. In a three-wave longitudinal study, we investigated how social networks and psychological adjustment coevolve within a group of international students enrolled in a coursework degree at the tertiary level. Using the Stochastic Actor-Oriented Model (SAOM), we identified the occurrences of social selection based on the levels of psychological and sociocultural adjustment. More specifically, students tended to deselect classmates who were dissimilar in their level of psychological adjustment and to befriend those who differed in their levels of sociocultural adjustment. In contrast, little evidence was found to suggest that features of social networks influenced students’ adjustment. Potential applications of this new method to future acculturation research are suggested.

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Zhou, Yingying, Baodong Cheng, and Jianbin Chen. "Uncovering the Effect of Forest Certification on the Dynamic Evolution of the Global Log Trade Network: A Stochastic Actor-Oriented Model Approach." Sustainability 14, no. 14 (July 6, 2022): 8229. http://dx.doi.org/10.3390/su14148229.

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Clarifying the dynamic evolution characteristics and driving mechanism of the global log trade network (GLTN) can provide references for the trade decision-making of various countries. Based on the stochastic actor-oriented model, this paper analyzed the GLTN’s dynamic evolution from 2010 to 2019 and paid more attention to the effect of forest certification on the dynamic evolution of the GLTN. Results indicate that from 2010 to 2019, many changes have occurred in the network. The change rate in the 2010–2015 period is faster than that in the 2015–2019 period. Countries tend to form reciprocity, three-cycles, and transitive trade ties over time. A country with more certified forest area tends to form new log export ties with the other countries. The trade imbalance ratio (TII) has a significant negative mediating effect on the evolutionary relationships between the certified forest area and the log trade network dynamic. Net exporters of log tend to avoid establishing export ties with countries with more certified forest areas over time. Countries with similar cultural backgrounds are easier to establish log trade ties with, while countries with farther geographical distances tend to avoid establishing trade ties over time. A free trade agreement (FTA) has a significant positive impact on the formation of log trade ties among nations. Our findings shed new light on the dynamic evolution mechanism of the global log trade network and offer implications for future trade and forest conservation policy design.

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Jung, Kyujin, Minsun Song, and Richard Feiock. "Isolated and Broken Bridges from Interorganizational Emergency Management Networks: An Institutional Collective Action Perspective." Urban Affairs Review 55, no. 3 (February 5, 2017): 950–75. http://dx.doi.org/10.1177/1078087417690257.

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We examine how interorganizational networks evolved after a disaster with an integrated approach that combines both social network perspectives and emergency management perspectives. This research describes changes in organizations that play a bridging role in interorganizational collaboration and examines endogenous and exogenous factors that lead organizations to be isolated during a disaster. Building from the Institutional Collective Action (ICA) framework, we argue that organizations that play the bridging role between two other organizations may fail to sustain their ties after a disaster. Because the bridging strategy involves risks, organizations are more likely to forge direct ties to other organizations that have resources they need rather than rely on bridges that they created before the disaster. We apply a stochastic actor-oriented model to show the dynamics of emergency management networks during the 2013 Seoul floods. This study contributes to understanding how the bridging strategy can be emasculated by endogenous and exogenous factors.

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FUJIMOTO, KAYO, TOM A. B. SNIJDERS, and THOMAS W. VALENTE. "Multivariate dynamics of one-mode and two-mode networks: Explaining similarity in sports participation among friends." Network Science 6, no. 3 (June 8, 2018): 370–95. http://dx.doi.org/10.1017/nws.2018.11.

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AbstractWe examined social mechanisms that account for similarity in the social context of school-sponsored extracurricular sports activities among friends. We distinguish two social mechanisms: “shared sports activities that lead to friendship,” whereby friendship formation and maintenance are conditioned by joint sports participation, and “friendship that leads to shared sports activities,” a form of social influence whereby adolescents join or maintain certain sports activities based on their friends' choices. Using a longitudinal sample of 1,776 10th graders at five high schools in Southern California, we employed a stochastic actor-oriented multivariate dynamic model to model the dynamic interplay between the two-mode affiliation network of adolescents' participation in sports activities and the one-mode friendship network. As a corresponding descriptive method, we propose a quantitative measure for the relative strength of the two-mentioned mechanisms as explanations of the association between the one-mode and the two-mode network. Further, we introduce two specifications that represent homophily effects in the two-mode network and apply them to test gender homophily in sports participation. The results provide strong evidence for both mechanisms, with friendship leading to shared sport activities as stronger than shared sports activities leading to friendships in explaining adolescents' friendships with co-participants.

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Colby, Darren. "Chaos from order: a network analysis of in-fighting before and after El Chapo’s arrest." Connections 41, no. 1 (January 1, 2021): 1–11. http://dx.doi.org/10.21307/connections-2021.023.

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Abstract The effect of leadership decapitation—the capture or killing of the leader of an armed group—on future violence has been studied with competing conclusions. In Mexico, leadership decapitation has been found to increase violence and in-fighting among drug cartels. However, the causal pathways between leadership decapitation and in-fighting are unclear. In this article, it is hypothesized that leadership decapitation will weaken alliances between armed actors, lead to greater preferential attachment in networks of cartels and militias, and result in greater transitive closure as cartels seek to expand their power. These hypotheses are tested with a stochastic actor oriented model on a network dataset of episodes of infighting among cartels and the militias formed to opposed them between the five years before and after Joaquín, “El Chapo” Guzmán Loera, the former leader of the Sinaloa Cartel, was arrested in 2016. The results show that alliances have virtually no effect on the decision of cartels and militias to fight each other; weaker organizations faced a higher reputational cost after El Chapo’s detention; and post-arrest cartel in-fighting did not increase as a result of uncertainty about the relative balance of power among cartels.

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Mon, Yi Yi, Seunghoo Lim, and Makoto Kakinaka. "Multiplex Relations between States: Coevolution of Trade Agreements and Political Alliances." Sustainability 11, no. 14 (July 18, 2019): 3911. http://dx.doi.org/10.3390/su11143911.

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The nature of interdependence between states encourages them to establish cooperation in different fields, leading to multiple relations. The policy alignments of states on trade and political relations can be regarded as the most critical agenda in a globalized world. Accounting for the linkages between economic and political issues, this study focuses on the two relational ties, (i) free trade agreements (FTAs) as economic cooperation and (ii) political alliances (PAs) as political cooperation. In addition, it evaluates the coevolution of FTAs and PAs by employing a multiplex stochastic actor-oriented model with longitudinal data of 160 countries during the period from 1990 to 2012. The results show that the presence of a PA inspires the formation of an FTA, but present no clear evidence that the presence of an FTA promotes the formation of a PA. Our analysis also shows that a state prefers to form both FTAs and PAs with trade hub partners that have more FTAs but prefers to form only PAs with political hub partners that have more PAs. This study argues that such asymmetric effects between FTAs and PAs emphasizes the preferences of states for liberalizing trade and connecting with partners that have many FTAs.

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Wiedemann, Nina, Henry Martin, and Martin Raubal. "Unlocking social network analysis methods for studying human mobility." AGILE: GIScience Series 3 (June 10, 2022): 1–12. http://dx.doi.org/10.5194/agile-giss-3-19-2022.

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Abstract. Planning and operations in urban spaces are strongly affected by human mobility behavior. A better understanding of individual mobility is key to improve transportation systems and to guide the allocation of public space. Previous studies have discovered statistical laws of travel distances, but the topology of movement between places has received little attention. We propose to employ network modelling methods to analyze the effect of spatial and context attributes on individual movement patterns. The perspective of mobility as a network allows to explicitly regard dyadic dependencies of sequential location visits. Here, we consider two methods developed for social networks and provide a formulation of mobility networks to justify their applicability. First, we use the Multiple Regression Quadratic Assignment Procedure to test hypotheses on the influence of location attributes on mobility behavior. Secondly, Stochastic Actor-Oriented Models are applied to model the evolution of mobility networks over time. As a proof-of-concept study, we transform data from one GNSS-based and one check-in based dataset into mobility networks and present results from both methods. We find relations that appear for a majority of samples and thus seem inherent to mobility networks. The differences between individuals and the available datasets are further quantified and discussed. We conclude that the transfer of network modeling methods is an interesting opportunity to study network-related phenomena in geographic information science.

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Nakazato, Hiromi, Rui Izumi, and Seunghoo Lim. "Joining Policy Forums Together to Develop Ki-no-Eki, a Community Currency System for Forest Management in Japan: Dynamics of Policy Communication Networks." Land 11, no. 10 (October 16, 2022): 1811. http://dx.doi.org/10.3390/land11101811.

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In some mountainous areas of Japan, the Ki-no-Eki system, in which wood is collected to thin the forest and is exchanged for community currency, has been specifically designed and implemented as a solution to current and emerging forest governance issues. This study aimed to capture the evolutionary processes of a complete communication network consisting of organizations that joined policy forums to help develop the Ki-no-Eki system. A total of 26 policy forums were held from 2011 to 2019 to discuss the adoption and implementation of the Ki-no-Eki system across Japan, and coattendance and the resultant policy discourses among 62 participating Ki-no-Eki organizations in these forums were regarded as dynamic communication network processes. We analyzed how policy communication networks formed and evolved to understand the underlying network dynamics driven by not only endogenous network processes—bonding and bridging social capital—but also exogenous effects defined by actors’ attributes. We employed the stochastic actor-oriented model for network dynamics to manage the collected longitudinal undirected network data. We found (i) the emergence of bonding social capital and (ii) homophilic and heterophilic connections in communication networks, which provided insightful explanations of the driving forces of social cohesion among Ki-no-Eki organizations engaged in forest management in Japan.

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Fang, Weipeng, Changwei Qin, Dan Zhou, Jian Yin, Zhongmin Liu, and Xianjun Guan. "The Impact of Cooperative Behavior between Social Organizations during the COVID-19 Pandemic Outbreak in Shanghai: A Simulation Approach." International Journal of Environmental Research and Public Health 20, no. 2 (January 12, 2023): 1409. http://dx.doi.org/10.3390/ijerph20021409.

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In 2022, a new outbreak of the COVID-19 pandemic created considerable challenges for the Shanghai public health system. However, conventional prevention and control strategies, which only rely on formal organizations, inefficiently decrease the number of infections. Thus, a multi-organization management mode is needed for pandemic prevention. In this paper, we applied a stochastic actor-oriented model (SAOM) to analyze how these social organizations cooperate with others and further identify the mechanism that drives them to create a reliable and sustainable cooperative relationship network from the perspective of social network analysis. The model allowed us to assess the effects of the actor’s attributes, the network structure, and dynamic cooperative behavior in RSiena with longitudinal data collected from 220 participants in 19 social organizations. The results indicated that the number of cooperative relationships increased during the pandemic, from 44 to 162, which means the network between social organizations became more reliable. Furthermore, all the hypotheses set in four sub-models were significant (t-ratio < 0.1, overall max t-ratio < 0.25, and e/s > 2). Additionally, the estimated values showed that four factors played a positive role in forming the cooperative relationship network, i.e., all except the “same age group effect (−1.02)”. The results also indicated that the social organizations tend to build relationships with more active actors in the community in every time period. This paper is of great significance regarding the innovation of public health system management and the improvement of Chinese grassroots governance.

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Snijders, Tom A. B. "Stochastic Actor-Oriented Models for Network Dynamics." Annual Review of Statistics and Its Application 4, no. 1 (March 7, 2017): 343–63. http://dx.doi.org/10.1146/annurev-statistics-060116-054035.

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Snijders, Tom A. B. "Stochastic actor‐oriented models for network change." Journal of Mathematical Sociology 21, no. 1-2 (April 1996): 149–72. http://dx.doi.org/10.1080/0022250x.1996.9990178.

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Pink, Sebastian, David Kretschmer, and Lars Leszczensky. "Choice modelling in social networks using stochastic actor-oriented models." Journal of Choice Modelling 34 (March 2020): 100202. http://dx.doi.org/10.1016/j.jocm.2020.100202.

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Lospinoso, Joshua A., Michael Schweinberger, Tom A. B. Snijders, and Ruth M. Ripley. "Assessing and accounting for time heterogeneity in stochastic actor oriented models." Advances in Data Analysis and Classification 5, no. 2 (November 5, 2010): 147–76. http://dx.doi.org/10.1007/s11634-010-0076-1.

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Amati, Viviana, Felix Schönenberger, and Tom A. B. Snijders. "Contemporaneous Statistics for Estimation in Stochastic Actor-Oriented Co-evolution Models." Psychometrika 84, no. 4 (July 15, 2019): 1068–96. http://dx.doi.org/10.1007/s11336-019-09676-3.

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Fisher, David N., Amiyaal Ilany, Matthew J. Silk, and Tom Tregenza. "Analysing animal social network dynamics: the potential of stochastic actor-oriented models." Journal of Animal Ecology 86, no. 2 (February 1, 2017): 202–12. http://dx.doi.org/10.1111/1365-2656.12630.

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Dokuka, Sofia. "Social Environment and Academic Performance: A Systematic Review of Stochastic Actor-Oriented Research." Sociological Journal 27, no. 3 (September 28, 2021): 175–91. http://dx.doi.org/10.19181/socjour.2021.27.3.8429.

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Academic achievements play an important role in an individual’s professional development, and are also considered one of the main characteristics of an education system. Academic achievements are associated with multiple factors, including the social environment of students. In this paper we review the studies that use stochastic actororiented models to examine the effects of social networks on academic achievements. We consider both the results and designs of existing studies and outline potential avenues for future research. We demonstrate that the majority of studies analyze the networks of positive relationships in schools. Only a few studies are based on data from universities. We also conclude that the majority of studies are based on data from western democracies. These findings can be considered as a basis for further empirical analysis.

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Shappell, Heather, Yorghos Tripodis, Ronald J. Killiany, and Eric D. Kolaczyk. "A paradigm for longitudinal complex network analysis over patient cohorts in neuroscience." Network Science 7, no. 2 (June 2019): 196–214. http://dx.doi.org/10.1017/nws.2019.9.

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AbstractThe study of complex brain networks, where structural or functional connections are evaluated to create an interconnected representation of the brain, has grown tremendously over the past decade. Many of the statistical network science tools for analyzing brain networks have been developed for cross-sectional studies and for the analysis of static networks. However, with both an increase in longitudinal study designs and an increased interest in the neurological network changes that occur during the progression of a disease, sophisticated methods for longitudinal brain network analysis are needed. We propose a paradigm for longitudinal brain network analysis over patient cohorts, with the key challenge being the adaptation of Stochastic Actor-Oriented Models to the neuroscience setting. Stochastic Actor-Oriented Models are designed to capture network dynamics representing a variety of influences on network change in a continuous-time Markov chain framework. Network dynamics are characterized through both endogenous (i.e. network related) and exogenous effects, where the latter include mechanisms conjectured in the literature. We outline an application to the resting-state functional magnetic resonance imaging setting with data from the Alzheimer’s Disease Neuroimaging Initiative study. We draw illustrative conclusions at the subject level and make a comparison between elderly controls and individuals with Alzheimer’s disease.

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Luo, Jinwen, Minjeong Jeon, Minho Lee, Eric Ho, Angela Fidler Pfammatter, Vivek Shetty, and Bonnie Spring. "Relationships between changing communication networks and changing perceptions of psychological safety in a team science setting: Analysis with actor-oriented social network models." PLOS ONE 17, no. 8 (August 31, 2022): e0273899. http://dx.doi.org/10.1371/journal.pone.0273899.

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A growing evidence base suggests that complex healthcare problems are optimally tackled through cross-disciplinary collaboration that draws upon the expertise of diverse researchers. Yet, the influences and processes underlying effective teamwork among independent researchers are not well-understood, making it difficult to fully optimize the collaborative process. To address this gap in knowledge, we used the annual NIH mHealth Training Institutes as a testbed to develop stochastic actor-oriented models that explore the communicative interactions and psychological changes of its disciplinarily and geographically diverse participants. The models help investigate social influence and social selection effects to understand whether and how social network interactions influence perceptions of team psychological safety during the institute and how they may sway communications between participants. We found a degree of social selection effects: in particular years, scholars were likely to choose to communicate with those who had more dissimilar levels of psychological safety. We found evidence of social influence, in particular, from scholars with lower psychological safety levels and from scholars with reciprocated communications, although the sizes and directions of the social influences somewhat varied across years. The current study demonstrated the utility of stochastic actor-oriented models in understanding the team science process which can inform team science initiatives. The study results can contribute to theory-building about team science which acknowledges the importance of social influence and selection.

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Cao, Dongping, Heng Li, Guangbin Wang, Xiaochun Luo, Xincong Yang, and Dan Tan. "Dynamics of Project-Based Collaborative Networks for BIM Implementation: Analysis Based on Stochastic Actor-Oriented Models." Journal of Management in Engineering 33, no. 3 (May 2017): 04016055. http://dx.doi.org/10.1061/(asce)me.1943-5479.0000503.

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Abderrazek Boukhris, Mohamed Bin. "Does Performance Homophily Matter in Acquisition Decisions? Evidence From Acquisition Network in the Global Electricity Industry." Journal of Social Sciences Research, no. 53 (March 10, 2019): 715–22. http://dx.doi.org/10.32861/jssr.53.715.722.

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In this paper I use data, that I have collected on corporate acquisition transactions among electricity companies worldwide during the period 1994-2004, to test the hypothesis of organizational performance homophily as an acquisition network-selection mechanism for firms in the electricity industry. I report clear evidence that performance considerations are taken into account by international electricity firms while choosing their network partners. The methodology used in this study is based on the stochastic actor- oriented models for social network analysis.

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Karell, Daniel, and Michael Freedman. "Sociocultural mechanisms of conflict: Combining topic and stochastic actor-oriented models in an analysis of Afghanistan, 1979–2001." Poetics 78 (February 2020): 101403. http://dx.doi.org/10.1016/j.poetic.2019.101403.

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Withers, Michael C., Michael D. Howard, and Laszlo Tihanyi. "You’ve Got a Friend: Examining Board Interlock Formation After Financial Restatements." Organization Science 31, no. 3 (May 2020): 742–69. http://dx.doi.org/10.1287/orsc.2019.1319.

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We investigate the impact of financial restatements as critical events that influence board interlock formation among Fortune 500 firms during the 2009–2013 period. Our empirical study is based on a longitudinal analysis of tie formation while accounting for dynamic changes in the behavior and characteristics of network nodes using stochastic actor-oriented models. We find that firms facing financial restatements experience disruption in network ties. However, social status helps mitigate these effects, and restating firms build new ties through socially embedded processes, such as reciprocity and transitivity. Our work contributes to the understanding of how interorganizational relationships are altered as a result of financial restatement events.

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Stadtfeld, Christoph, Tom A. B. Snijders, Christian Steglich, and Marijtje van Duijn. "Statistical Power in Longitudinal Network Studies." Sociological Methods & Research 49, no. 4 (May 1, 2018): 1103–32. http://dx.doi.org/10.1177/0049124118769113.

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Longitudinal social network studies can easily suffer from insufficient statistical power. Studies that simultaneously investigate change of network ties and change of nodal attributes (selection and influence studies) are particularly at risk because the number of nodal observations is typically much lower than the number of observed tie variables. This article presents a simulation-based procedure to evaluate statistical power of longitudinal social network studies in which stochastic actor-oriented models are to be applied. Two detailed case studies illustrate how statistical power is strongly affected by network size, number of data collection waves, effect sizes, missing data, and participant turnover. These issues should thus be explored in the design phase of longitudinal social network studies.

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Ivaniushina, Valeria, and Vera Titkova. "Peer influence in adolescent drinking behavior: A meta-analysis of stochastic actor-based modeling studies." PLOS ONE 16, no. 4 (April 16, 2021): e0250169. http://dx.doi.org/10.1371/journal.pone.0250169.

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Objectives To measure the effects of peer influence and peer selection on drinking behavior in adolescence through a rigorous statistical approach designed to unravel these interrelated processes. Methods We conducted systematic searches of electronic databases, thesis collections and conference proceedings to identify studies that used longitudinal network design and stochastic actor-oriented modeling to analyze drinking behavior in adolescents. Parameter estimates collected from individual studies were analyzed using multilevel random-effects models. Results We identified 26 articles eligible for meta-analysis. Meta-analyses for different specifications of the peer influence effect were conducted separately. The peer influence effect was positive for every specification: for average similarity (avSim) mean log odds ratio was 1.27 with 95% confidence interval [0.04; 2.49]; for total similarity (totSim) 0.46 (95% CI = [0.44; 0.48]), and for average alter (avAlt) 0.70 (95% CI = [-0.01; 1.41]). The peer selection effect (simX) was also positive: 0.46 (95% CI = [0.28; 0.63]). Conversion log odds ratio values to Cohen’s d gives estimates from 0.25 to 0.70, which is considered as medium to large effect. Conclusions Advances in methodology for social network analysis have made it possible to accurately estimate peer influence effects free from peer selection effects. More research is necessary to clarify the roles of age, gender, and individual susceptibility on the changing behavior of adolescents under the influence of their peers. Understanding the effects of peer influence should inform practitioners and policy makers to design and deliver more effective prevention programs.

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Boda, Zsófia, Bálint Néray, and Tom A. B. Snijders. "The Dynamics of Interethnic Friendships and Negative Ties in Secondary School: The Role of Peer-Perceived Ethnicity." Social Psychology Quarterly 83, no. 4 (August 7, 2020): 342–62. http://dx.doi.org/10.1177/0190272520907594.

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This study examines ethnic integration in secondary school. Social identity theory suggests that perception of relevant individual attributes plays a crucial role in defining ingroups and outgroups, contributing to befriending, and disliking others. Therefore, we analyze the role of peer-perceived ethnicity in social ties. Networks of friendship, dislike, and perceived ethnicity were modeled together using dynamic stochastic actor-oriented models, separating the effect of perceived ethnicity on social ties from that of social ties on perceived ethnicity. Data came from a Hungarian sample of 12 school classes with one minority group: the Roma. Treating friendship and dislike as mutually exclusive and comparing them to neutral relations, we found evidence for the role of perceived ethnicity in dislike—majority students disliked those they perceived as minority peers. However, we saw no direct effect of ethnicity on the friendship network. Implications of the joint modeling of mutually exclusive relationship aspects are discussed.

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Leszczensky, Lars, and Sebastian Pink. "Are Birds of a Feather Praying Together? Assessing Friends’ Influence on Muslim Youths’ Religiosity in Germany." Social Psychology Quarterly 83, no. 3 (August 12, 2020): 251–71. http://dx.doi.org/10.1177/0190272520936633.

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Muslim religiosity is often portrayed as a barrier to integration into secular societies, especially in Europe. Scholars suggest that religiously segregated networks reinforce Muslims’ religiosity and religious identification, but solid evidence is scarce. Based on longitudinal German data, we examined whether friendship networks influence Muslim youths’ religiosity. Using stochastic actor-oriented models, we also assessed whether religiosity in turn relates to friendship choices. We found that higher shares of Muslim friends neither increase Muslim youths’ religious identification nor their frequency of prayer, but they are associated with more frequent mosque attendance. Furthermore, Muslim youths assimilated their Muslim friends’ mosque attendance and frequency of prayer. Friends’ actual religious practices, rather than shared group membership, thus seems to shape individual religiosity. Finally, religiosity does not hamper interreligious friendships; it was unrelated to friendship choices. Results are similar for Christian youths, suggesting that these patterns are not unique to Muslims.

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Raabe, Isabel J., Zsófia Boda, and Christoph Stadtfeld. "The Social Pipeline: How Friend Influence and Peer Exposure Widen the STEM Gender Gap." Sociology of Education 92, no. 2 (January 29, 2019): 105–23. http://dx.doi.org/10.1177/0038040718824095.

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Individuals’ favorite subjects in school can predetermine their educational and occupational careers. If girls develop weaker preferences for science, technology, engineering, and math (STEM), it can contribute to macrolevel gender inequalities in income and status. Relying on large-scale panel data on adolescents from Sweden (218 classrooms, 4,998 students), we observe a widening gender gap in preferring STEM subjects within a year (girls, 19 to 15 percent; boys, 21 to 20 percent). By applying newly developed random-coefficient multilevel stochastic actor-oriented models on social network data (27,428 friendships), we investigate how social context contributes to those changes. We find strong evidence that students adjust their preferences to those of their friends (friend influence). Moreover, girls tend to retain their STEM preferences when other girls in their classroom also like STEM (peer exposure). We conclude that these mechanisms amplify preexisting preferences and thereby contribute to the observed dramatic widening of the STEM gender gap.

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Bichler, Gisela, Alexis Norris, and Citlalik Ibarra. "Evolving Patterns of Aggression: Investigating the Structure of Gang Violence during the Era of Civil Gang Injunctions." Social Sciences 9, no. 11 (November 11, 2020): 203. http://dx.doi.org/10.3390/socsci9110203.

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Mapping the structural characteristics of attack behavior, this study explores how violent conflict evolved with the implementation of civil gang injunctions (CGIs). Networks were generated by linking defendants and victims named in 963 prosecutions involving street gangs active in the City of Los Angeles (1998–2013). Aggregating directed ties to 318 groups associated with the combatants, we compare four observations that correspond with distinct phases of CGI implementation—development (1998–2001), assent (2002–2005), maturity (2006–2009), and saturation (2010–2013). Using a triad census to calculate a ratio of simple patterns (retaliation, directed lines, and out-stars) to complex three-way interactions, we observed that CGIs were associated with a substantive thickening of conflict—greater complexity was found in conflict relations over time. Dissecting the nature of change, stochastic actor-oriented models (SAOMs) show that enjoined gangs are more likely to initiate transitive closure. The findings suggest that crime control efforts must make regular adjustments in response to the evolving structure of gang interactions.

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la Roi, Chaïm, Jan Kornelis Dijkstra, Tina Kretschmer, Rūta Savickaitė, and René Veenstra. "Peers and Homophobic Attitudes in Adolescence: Examining Selection and Influence Processes in Friendships and Antipathies." Journal of Youth and Adolescence 49, no. 11 (August 13, 2020): 2229–45. http://dx.doi.org/10.1007/s10964-020-01298-8.

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Abstract Homophobic attitudes and behavior are a widespread problem among adolescents, but what the role of peer relationships such as friendships and antipathies is in shaping these attitudes remains unclear. Therefore, this study examined to what extent homophobic attitudes are influenced by friends’ and foes’ homophobic attitudes, and whether homophobic attitudes serve as a selection criterion for the formation of friendships and antipathies. Participants came from three Dutch high schools across two waves (wave 1 November 2014, wave 2 March/April 2015, ages 11–20, N = 1935, 51.5% girls). Stochastic actor-oriented models were estimated for testing hypotheses. The results showed that adolescents adjusted their homophobic attitudes to their friends’ homophobic attitudes, but homophobic attitudes were not consistently related to friendship selection. Further, findings indicated that being dissimilar in homophobic attitudes increased the likelihood to dislike cross-sex peers. Together, the findings suggest that adolescents’ homophobic attitudes were to some extent subject to peer influence, but homophobic attitudes did not steer who adolescents befriended or disliked.

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BLOCK, PER, and THOMAS GRUND. "Multidimensional homophily in friendship networks." Network Science 2, no. 2 (August 2014): 189–212. http://dx.doi.org/10.1017/nws.2014.17.

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AbstractHomophily—the tendency for individuals to associate with similar others—is one of the most persistent findings in social network analysis. Its importance is established along the lines of a multitude of sociologically relevant dimensions, e.g. sex, ethnicity and social class. Existing research, however, mostly focuses on one dimension at a time. But people are inherently multidimensional, have many attributes and are members of multiple groups. In this article, we explore such multidimensionality further in the context of network dynamics. Are friendship ties increasingly likely to emerge and persist when individuals have an increasing number of attributes in common? We analyze eleven friendship networks of adolescents, draw on stochastic actor-oriented network models and focus on the interaction of established homophily effects. Our results indicate that main effects for homophily on various dimensions are positive. At the same time, the interaction of these homophily effects is negative. There seems to be a diminishing effect for having more than one attribute in common. We conclude that studies of homophily and friendship formation need to address such multidimensionality further.

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Leszczensky, Lars, and Sebastian Pink. "What Drives Ethnic Homophily? A Relational Approach on How Ethnic Identification Moderates Preferences for Same-Ethnic Friends." American Sociological Review 84, no. 3 (May 9, 2019): 394–419. http://dx.doi.org/10.1177/0003122419846849.

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Individual preferences for same-ethnic friends contribute to persistent segregation of adolescents’ friendship networks. Yet, we know surprisingly little about the mechanisms behind ethnic homophily. Prior research suggests that ethnic homophily is ubiquitous, but a social identity perspective indicates that strong ingroup identification drives ingroup favoritism. Combining a social identity perspective with a relational approach, we ask whether the presumed increased homophily of high identifiers extends to all ingroup members, or whether it is conditional on the strength of same-ethnics’ identification. We propose that the strength of ethnic identification affects not only how much individuals desire same-ethnic friends, but also how attractive they are as potential friends to others. Fitting stochastic actor-oriented models to German adolescent school-based network panel data, we find that ethnic homophily is driven by an interplay of peers’ ethnic identification: high identifiers befriend same-ethnic peers who share their strong ethnic identification, while excluding same-ethnic low identifiers. Low identifiers, in turn, tend to avoid befriending inter-ethnic high identifiers. Our relational approach reveals that ethnic homophily is hardly ubiquitous but requires strong identification of both parties of a (potential) friendship.

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Kindschi, Martin, Jan Cieciuch, Eldad Davidov, Alexander Ehlert, Heiko Rauhut, Claudio Juan Tessone, and René Algesheimer. "Values in adolescent friendship networks." Network Science 7, no. 4 (September 23, 2019): 498–522. http://dx.doi.org/10.1017/nws.2019.16.

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AbstractValues—the motivational goals that define what is important to us—guide our decisions and actions every day. Their importance is established in a long line of research investigating their universality across countries and their evolution from childhood to adulthood. In adolescence, value structures are subject to substantial change, as life becomes increasingly social. Value change has thus far been understood to operate independently within each person. However, being embedded in various social systems, adolescents are constantly subject to social influence from peers. Thus, we introduce a framework investigating the emergence and evolution of value priorities in the dynamic context of friendship networks. Drawing on stochastic actor-oriented network models, we analyze 73 friendship networks of adolescents. Regarding the evolution of values, we find that adolescents’ value systems evolve in a continuous cycle of internal validation through the selection and enactment of goals—thereby experiencing both congruence and conflicts—and external validation through social comparison among their friends. Regarding the evolution of friendship networks, we find that demographics are more salient for the initiation of new friendships, whereas values are more relevant for the maintenance of existing friendships.

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Ivaniushina, Valeria, Vera Titkova, and Daniel Alexandrov. "Peer influence in adolescent drinking behaviour: a protocol for systematic review and meta-analysis of stochastic actor-based modeling studies." BMJ Open 9, no. 7 (July 2019): e028709. http://dx.doi.org/10.1136/bmjopen-2018-028709.

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IntroductionAlcohol consumption is a considerable public health problem that is especially harmful to young people. To develop effective prevention programmes targeted at adolescents, it is important to understand the social mechanisms triggering alcohol consumption. Among such mechanisms, peer influence plays an important role. The effects of peer influence are very difficult to evaluate because of the entanglement with social selection, that is, a tendency of people to befriend others with similar behaviour. The recently developed stochastic actor-oriented models (SAOM) approach is designed to disentangle social influence from social selection. The aim of this study is to conduct a systematic review and meta-analysis of studies employing SAOM methodology to evaluate the effects of social influence on adolescent drinking behaviour.Methods and analysisIn order to analyse the co-evolution of alcohol consumption and adolescent friendship networks, we will collect articles that use SAOM methodology through systematic electronic searches in Web of Science, Scopus, PubMed, The Cochrane Library (Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials), EBSCOhost (MEDLINE, SocINDEX, Academic Source, ERIC), ProQuest (ProQuest Dissertations and Theses Global), PsycINFO (PsycNET), Excerpta Medica database (Embase) and Cumulative Index to Nursing and Allied Health Literature (CINAHL). We will collect the literature from academic journals, dissertations/theses, reports and conference materials. Three reviewers will retrieve and independently assess potentially relevant material in terms of whether they comply with prespecified criteria. Subsequently, we will summarise the results of the studies in a systematic review. If a sufficient number of studies can be found, SAOM quantitative results will be extracted and meta-analysed. The project will go from 1 December 2018 to 1 December 2019.Ethics and disseminationEthical approval will not be required as our work is based on published studies. A list of all the studies included in this work will be available for review. We plan dissemination in a peer-reviewed international scientific journal and through conference presentations. Our review will highlight the peer effect of peers in adolescent drinking behaviour and provide guidance for developing effective prevention and intervention programmes. We expect it to be informative for policy and practice, decision-making as well as for further research in public health and sociology of adolescents.PROSPERO registration numberCRD42019119836.

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Fu, Lin, Yue Fan, Jin Cheng, Hao Zheng, and Zhengkui Liu. "Being Popular or Having Popular Friends, Which Is Better? A Longitudinal Social Network Analysis of Depressive Symptoms among Chinese Adolescents under Major Chronic Stress." International Journal of Environmental Research and Public Health 18, no. 21 (October 24, 2021): 11164. http://dx.doi.org/10.3390/ijerph182111164.

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Background: Previous studies have found that adolescents’ depressive symptoms are influenced by social networks in a stressful context, especially focusing on the processes of social selection and social influence. The current study aimed to explore the coevolution of sociometric popularity and depressive symptoms among adolescents suffering from the stress attached to the Chinese gaokao. Methods: The analytical sample comprised 1062 Chinese adolescents who were under significant pressure to return to school for an additional year (returnees) to prepare for college entrance examinations. Students were assessed for depressive symptoms and asked to nominate up to five friends within their classes across four waves (six months). We employed stochastic actor-oriented models to investigate the interdependent relationships between popularity and depressive symptoms. Results: Adolescents’ depressive symptoms negatively predicted future friendship popularity in this stressful situation, but not vice versa. The results of this study also highlighted the importance of friends’ popularity, indicating that adolescents who nominated popular peers as friends tended to subsequently have lower depressive symptoms. Conclusion: These findings suggested that friends’ popularity may serve as a protective factor against depressive symptoms under major chronic stress. Network-based interventions may have practical implications for reducing depressive symptoms under major chronic stress.

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Hunt, Edmund R., Brian Mi, Camila Fernandez, Brandyn M. Wong, Jonathan N. Pruitt, and Noa Pinter-Wollman. "Social interactions shape individual and collective personality in social spiders." Proceedings of the Royal Society B: Biological Sciences 285, no. 1886 (September 5, 2018): 20181366. http://dx.doi.org/10.1098/rspb.2018.1366.

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The behavioural composition of a group and the dynamics of social interactions can both influence how social animals work collectively. For example, individuals exhibiting certain behavioural tendencies may have a disproportionately large impact on the group, and so are referred to as keystone individuals, while interactions between individuals can facilitate information transmission about resources. Despite the potential impact of both behavioural composition and interactions on collective behaviour, the relationship between consistent behaviours (also known as personalities) and social interactions remains poorly understood. Here, we use stochastic actor-oriented models to uncover the interdependencies between boldness and social interactions in the social spider Stegodyphus dumicola . We find that boldness has no effect on the likelihood of forming social interactions, but interactions do affect boldness, and lead to an increase in the boldness of the shyer individual. Furthermore, spiders tend to interact with the same individuals as their neighbours. In general, boldness decreases over time, but once an individual's boldness begins to increase, this increase accelerates, suggesting a positive feedback mechanism. These dynamics of interactions and boldness result in skewed boldness distributions of a few bold individuals and many shy individuals, as observed in nature. This group behavioural composition facilitates efficient collective behaviours, such as rapid collective prey attack. Thus, by examining the relationship between behaviour and interactions, we reveal the mechanisms that underlie the emergence of adaptive group composition and collective behaviour.

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ELMER, TIMON, ZSÓFIA BODA, and CHRISTOPH STADTFELD. "The co-evolution of emotional well-being with weak and strong friendship ties." Network Science 5, no. 3 (August 7, 2017): 278–307. http://dx.doi.org/10.1017/nws.2017.20.

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AbstractSocial ties are strongly related to well-being. But what characterizes this relationship? This study investigates social mechanisms explaining how social ties affect well-being through social integration and social influence, and how well-being affects social ties through social selection. We hypothesize that highly integrated individuals–those with more extensive and dense friendship networks–report higher emotional well-being than others. Moreover, emotional well-being should be influenced by the well-being of close friends. Finally, well-being should affect friendship selection when individuals prefer others with higher levels of well-being, and others whose well-being is similar to theirs. We test our hypotheses using longitudinal social network and well-being data of 117 individuals living in a graduate housing community. The application of a novel extension of Stochastic Actor-Oriented Models for ordered networks (ordered SAOMs) allows us to detail and test our hypotheses for weak- and strong-tied friendship networks simultaneously. Results do not support our social integration and social influence hypotheses but provide evidence for selection: individuals with higher emotional well-being tend to have more strong-tied friends, and there are homophily processes regarding emotional well-being in strong-tied networks. Our study highlights the two-directional relationship between social ties and well-being, and demonstrates the importance of considering different tie strengths for various social processes.

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Vermond, Debbie, Esther de Groot, Valerie A. Sills, Georgios Lyratzopoulos, Fiona M. Walter, Niek J. de Wit, and Greg Rubin. "The evolution and co-evolution of a primary care cancer research network: From academic social connection to research collaboration." PLOS ONE 17, no. 7 (July 29, 2022): e0272255. http://dx.doi.org/10.1371/journal.pone.0272255.

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Academic networks are expected to enhance scientific collaboration and thereby increase research outputs. However, little is known about whether and how the initial steps of getting to know other researchers translates into effective collaborations. In this paper, we investigate the evolution and co-evolution of an academic social network and a collaborative research network (using co-authorship as a proxy measure of the latter), and simultaneously examine the effect of individual researcher characteristics (e.g. gender, seniority or workplace) on their evolving relationships. We used longitudinal data from an international network in primary care cancer research: the CanTest Collaborative (CanTest). Surveys were distributed amongst CanTest researchers to map who knows who (the ‘academic social network’). Co-authorship relations were derived from Scopus (the ‘collaborative network’). Stochastic actor-oriented models were employed to investigate the evolution and co-evolution of both networks. Visualizing the development of the CanTest network revealed that researchers within CanTest get to know each other quickly and also start collaborating over time (evolution of the academic social network and collaborative network respectively). Results point to a stable and solid academic social network that is particularly encouraging towards more junior researchers; yet differing for male and female researchers (the effect of individual researcher characteristics). Moreover, although the academic social network and the research collaborations do not grow at the same pace, the benefit of creating academic social relationships to stimulate effective research collaboration is clearly demonstrated (co-evolution of both networks).

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Milewicz, Karolina, James Hollway, Claire Peacock, and Duncan Snidal. "Beyond Trade." Journal of Conflict Resolution 62, no. 4 (September 23, 2016): 743–73. http://dx.doi.org/10.1177/0022002716662687.

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Increased complexity and density of transnational problems create unprecedented challenges and opportunities for contemporary international governance. “Issue linkage” is one institutional arrangement through which states address these changing circumstances. In this article, we examine the widening scope of the nontrade agenda in preferential trade agreements (PTAs). Nontrade issues (NTIs) such as human rights, democracy, environment, corruption, and labor standards are increasingly linked to PTAs. This issue linkage has important implications for understanding changing patterns of international trade, including the shift to PTAs and the rise of NTIs. We show that (1) states’ choices to commit to bilateral or plurilateral versions of traditional PTAs and to PTAs with NTIs are highly interdependent, (2) states increasingly incorporate NTIs into PTAs, as the associated costs of policy change are lowered through earlier agreements, and (3) network pressures favor the increasing adoption of bilateral and especially plurilateral NTIs over time. Using an original data set on NTIs covering 522 PTAs and spanning the period 1951 to 2009, we evaluate states’ motives behind the widening nontrade agenda of trade agreements using longitudinal network modeling. We employ multiplex coevolution stochastic actor-oriented network models in a novel design to account for interdependencies within and across states’ decisions. Following a descriptive mapping of major NTIs, we evaluate our theoretical arguments. Testing against the alternative explanations of power and commitment, we find that endogenous cost considerations are the most significant factor explaining the inclusion of NTIs into PTAs.

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Pilny, Andrew, Luisa Ruge-Jones, and Marshall Scott Poole. "A tutorial for modeling the evolution of network dynamics for multiple groups." Frontiers in Human Dynamics 4 (January 20, 2023). http://dx.doi.org/10.3389/fhumd.2022.982066.

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Researchers have been increasingly taking advantage of the stochastic actor-oriented modeling framework as a method to analyze the evolution of network ties. Although the framework has proven to be a useful method to model longitudinal network data, it is designed to analyze a sample of one bounded network. For group and team researchers, this can be a significant limitation because such researchers often collect data on more than one team. This paper presents a nontechnical and hands-on introduction for a meta-level technique for stochastic actor-oriented models in RSIENA where researchers can simultaneously analyze network drivers from multiple samples of teams and groups. Moreover, we follow up with a multilevel Bayesian version of the model when it is appropriate. We also provide a framework for researchers to understand what types of research questions and theories could be examined and tested.

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Journal articles on the topic 'Stochastic-actor oriented model'

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