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  • 1.
    Block, Per
    et al.
    ETH Zurich, Switzerland.
    Koskinen, Johan
    University of Manchester, UK.
    Hollway, James
    Geneva University, Switzerland.
    Steglich, Christian
    Linköping University, Department of Management and Engineering, The Institute for Analytical Sociology, IAS. Linköping University, Faculty of Arts and Sciences. University of Groningen, The Netherlands.
    Stadtfeld, Christoph
    ETH Zurich, Switzerland.
    Change we can believe in: Comparing longitudinal network modelson consistency, interpretability and predictive power2018In: Social Networks, ISSN 0378-8733, E-ISSN 1879-2111, Vol. 52, p. 180-191Article in journal (Refereed)
    Abstract [en]

    While several models for analysing longitudinal network data have been proposed, their main differ-ences, especially regarding the treatment of time, have not been discussed extensively in the literature.However, differences in treatment of time strongly impact the conclusions that can be drawn from data.In this article we compare auto-regressive network models using the example of TERGMs – a temporalextensions of ERGMs – and process-based models using SAOMs as an example. We conclude that theTERGM has, in contrast to the ERGM, no consistent interpretation on tie-level probabilities, as well as noconsistent interpretation on processes of network change. Further, parameters in the TERGM are stronglydependent on the interval length between two time-points. Neither limitation is true for process-basednetwork models such as the SAOM. Finally, both compared models perform poorly in out-of-sampleprediction compared to trivial predictive models.

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  • 2.
    Collet, Francois
    et al.
    ESADE Business School, Barcelona, Spain.
    Hedström, Peter
    Institute for Futures Studies, Stockholm, Sweden.
    Old friends and new acquaintances: Tie formation mechanisms in an inter-organizational network generated by employee mobility2013In: Social Networks, ISSN 0378-8733, E-ISSN 1879-2111, Vol. 35, no 3, p. 288-299Article in journal (Refereed)
    Abstract [en]

    This study investigates mechanisms of tie formation in an interorganizational network generated by the mobility of employees between organizations. We analyze a data set that contains information on all organizations in the Stockholm metropolitan area between 1990 and 2003. We show that the formation of new ties is contingent upon the direction of past ties, and that most connections occur at an intermediate geodesic distance of 2 and 3. The findings highlight the importance of tie direction and indirect connections in research on network dynamics and knowledge exchanges stemming from the mobility of employees across organizations.

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  • 3.
    Habinek, Jacob
    et al.
    University of California, Berkeley, Department of Sociology, United States.
    Martin, John Levi
    University of Chicago, Department of Sociology, United States.
    Zablocki, Benjamin
    Rutgers University, Department of Sociology, United States.
    Double-embeddedness: Spatial and relational contexts of tie persistence and re-formation2015In: Social Networks, ISSN 0378-8733, E-ISSN 1879-2111, Vol. 42, p. 27-41Article in journal (Refereed)
    Abstract [en]

    Personal relationships are embedded in both spatial and relational contexts. Using data on 60 intentional communities from the Urban Communes Data Set, we examine how such embedding is related to the persistence and re-formation of close personal ties over a thirteen year period, beginning from when most members had been out of their group environments more than a decade. We find that local network structure—the pattern of dyads immediately surrounding any dyad—is extremely weighty in which ties persist, which lapse, and which are re-initiated, but that the precise ways in which local structure affects contact are bound up with the distance between dyad members. We also find asymmetries in these processes that other studies have been unable to uncover—that processes that lead ties to be dropped are not the same as those that lead them to be renewed; that increases in local embeddedness are not opposite of decreases; that change in contact is not the same as change in friendship. Finally, there is evidence of hierarchical effects influencing the retention of friendships more than twenty-five years after most respondents left their groups.

  • 4.
    Krause, Robert
    et al.
    Linköping University, Department of Management and Engineering, The Institute for Analytical Sociology, IAS. Linköping University, Faculty of Arts and Sciences.
    Huisman, Mark
    Univ Groningen, Netherlands.
    Steglich, Christian
    Linköping University, Department of Management and Engineering, The Institute for Analytical Sociology, IAS. Linköping University, Faculty of Arts and Sciences. Univ Groningen, Netherlands.
    Snijders, Tom
    Univ Groningen, Netherlands; Univ Oxford, England.
    Missing data in cross-sectional networks - An extensive comparison of missing data treatment methods2020In: Social Networks, ISSN 0378-8733, E-ISSN 1879-2111, Vol. 62, p. 99-112Article in journal (Refereed)
    Abstract [en]

    This paper compares several missing data treatment methods for missing network data on a diverse set of simulated networks under several missing data mechanisms. We focus the comparison on three different outcomes: descriptive statistics, link reconstruction, and model parameters. The results indicate that the often used methods (analysis of available cases and null-tie imputation) lead to considerable bias on descriptive statistics with moderate or large proportions of missing data. Multiple imputation using sophisticated imputation models based on exponential random graph models (ERGMs) lead to acceptable biases in descriptive statistics and model parameters even under large amounts of missing data. For link reconstruction multiple imputation by simple ERGM performed well on small data sets, while missing data was more accurately imputed in larger data sets with multiple imputation by complex Bayesian ERGMs (BERGMs).

  • 5.
    Nordlund, Carl
    Central European University, Budapest, Hungary.
    A deviational approach to blockmodeling of valued networks2016In: Social Networks, ISSN 0378-8733, E-ISSN 1879-2111, Vol. 44, p. 160-178Article in journal (Refereed)
    Abstract [en]

    This article proposes a novel approach to blockmodeling of valued (one-mode) networks where the identification of (binary) block patterns in the valued relations differ from existing approaches. Rather than looking at the absolute values of relations, or examining valued ties on a per-actor basis (cf. Nordlund, 2007), the approach identifies prominent (binary) ties on the basis of deviations from expected values. By comparing the distribution of each actor's valued relations to its alters with the macro-level distributions of total in- and outdegrees, prominent (1) and non-prominent (0) ties are determined both on a per-actor-to-actor and a per-actor-from-actor basis. This allows for a direct interpretation of the underlying functional anatomy of a non-dichotomized valued network using the standard set of ideal blocks as found in generalized blockmodeling of binary networks.

    In addition to its applicability for direct blockmodeling, the article also suggests a novel indirect measure of deviational structural equivalence on the basis of such deviations from expected values.

    Exemplified with the note-sharing data in Žiberna (2007a), citations among social work journals (Baker, 1992), and total commodity trade among EU/EFTA countries as of 2010, both the direct and indirect approach produce results that are more sensitive to variations at the dyadic level than existing approaches. This is particularly evident in the case of the EU/EFTA trade network, where the indirect approach yields partitions and blockmodels in support of theories of regional trade, despite the significantly skewed valued degree distribution of the dataset.

  • 6.
    Nordlund, Carl
    Linköping University, Department of Management and Engineering, The Institute for Analytical Sociology, IAS. Linköping University, Faculty of Arts and Sciences.
    Direct blockmodeling of valued and binary networks: a dichotomization-free approach2020In: Social Networks, ISSN 0378-8733, E-ISSN 1879-2111, Vol. 61, p. 128-143Article in journal (Refereed)
    Abstract [en]

    A long-standing open problem with direct blockmodeling is that it is explicitly intended for binary, not valued, networks. The underlying dilemma is how empirical valued blocks can be compared with ideal binary blocks, an intrinsic problem in the direct approach where partitions are solely determined through such comparisons. Addressing this dilemma, valued networks have either been dichotomized into binary versions, or novel types of ideal valued blocks have been introduced. Both these workarounds are problematic in terms of interpretability, unwanted data reduction, and the often arbitrary setting of model parameters. This paper proposes a direct blockmodeling approach that effectively bypasses the dilemma with blockmodeling of valued networks. By introducing an adaptive weighted correlation-based criteria function, the proposed approach is directly applicable to both binary and valued networks, without any form of dichotomization or transformation of the valued (or binary) data at any point in the analysis, while still using the conventional set of ideal binary blocks from structural, regular and generalized blockmodeling. The proposed approach seemingly solves two other open problems with direct blockmodeling. First, its standardized goodness-of-fit measure allows for direct comparisons across solutions, within and between networks of different sizes, value types, and notions of equivalence. Secondly, through an inherent bias of point-biserial correlations, the approach puts a premium on solutions that are closer to the mid-point density of blockmodels. This, it is argued, translates into solutions that are more intuitive and easier to interpret. The approach is demonstrated by structural, regular and generalized blockmodeling applications of six classical binary and valued networks. Finding feasible and intuitive optimal solutions in both the binary and valued examples, the approach is proposed not only as a practical, dichotomization-free heuristic for blockmodeling of valued networks but also, through its additional benefits, as an alternative to the conventional direct approach to blockmodeling.

    The full text will be freely available from 2021-12-25 06:00
  • 7.
    Stadtfeld, Christoph
    et al.
    Swiss Fed Inst Technol, Switzerland.
    Takács, Károly
    Linköping University, Department of Management and Engineering, The Institute for Analytical Sociology, IAS. Linköping University, Faculty of Arts and Sciences. Computat Social Sci Res Ctr Educ and Network Studie, Hungary.
    Voros, Andras
    Swiss Fed Inst Technol, Switzerland; Univ Manchester, England; Univ Manchester, England.
    The Emergence and Stability of Groups in Social Networks2020In: Social Networks, ISSN 0378-8733, E-ISSN 1879-2111, Vol. 60, p. 129-145Article in journal (Refereed)
    Abstract [en]

    An important puzzle in social network research is to explain how macro-level structures emerge from micro-level network processes. Explaining the emergence and stability of structural groups in social networks is particularly difficult for two reasons. First, because groups are characterized both by high connectedness within (group cohesion) and lack of connectedness between them (group boundaries). Second, because a large number of theoretical micro-level network processes contribute to their emergence. We argue that traditional social network theories that are concerned with the evolution of positive relations (forces of attraction) are not sufficient to explain the emergence of groups because they lack mechanisms explaining the emergence of group boundaries. Models that additionally account for the evolution of negative ties (forces of repulsion) may be better suited to explain the emergence and stability of groups. We build a theoretical model and illustrate its usefulness by fitting stochastic actor-oriented models (SAOMs) to empirical data of co-evolving networks of friendship and dislike among 479 secondary-school students. The SAOMs include a number of newly developed effects expressing the co-evolution between positive and negative ties. We then simulate networks from the estimated models to explore the micro-macro link. We find that a model that considers forces of attraction and repulsion simultaneously is better at explaining groups in social networks. In the long run, however, the empirically informed simulations generate networks that are too stylized to be realistic, raising further questions about model degeneracy and time heterogeneity of group processes.

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  • 8.
    van der Ploeg, Rozemarijn
    et al.
    Department of Sociology, University of Groningen, Groningen, the Netherlands.
    Steglich, Christian
    Linköping University, Department of Management and Engineering, The Institute for Analytical Sociology, IAS. Linköping University, Faculty of Arts and Sciences.
    Veenstra, René
    Department of Sociology, University of Groningen, Groningen, the Netherlands.
    The way bullying works: How new ties facilitate the mutual reinforcement of status and bullying in elementary schools2020In: Social Networks, ISSN 0378-8733, E-ISSN 1879-2111, Vol. 60, p. 71-82Article in journal (Refereed)
    Abstract [en]

    This study addresses the puzzle how high-status bullies in elementary school are able to maintain high status among their classmates despite bullying (some of) them. The dynamic interplay between bullying and status was studied, focusing on how relational bullying affects the creation, dissolution, and maintenance of status attributions, and vice versa. Longitudinal round-robin peer nomination data were obtained from 82 school classes in15 Dutch elementary schools (2055 students; 50% boys) followed over three yearly measurements, starting out in grades 2–5 when students were aged 8-11. An age-dependent effect of bullying on the creation of new status attributions was found. Whereas the youngest group punished bullying by a refusal to attribute status to the bully, this turned into a reward of bullying in the oldest groups. Unexpectedly, high-status bullies seemed to avoid continual bullying of the same victims, pointing to explanations of why their status can persist.

    The full text will be freely available from 2021-01-11 17:54
1 - 8 of 8
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