Univariate and multivariate models of positive and negative networks: Liking, disliking, and bully–victim relationships

Huitsing, Gijs; Duijn, Marijtje van; Snijders, Tom A. B.; Wang, Peng; Sainio, Miia; Salmivalli, Christina; Veenstra, René

doi:10.1016/j.socnet.2012.08.001

Cited by 119 publications

(109 citation statements)

References 45 publications

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“…Besides status-related ones, many other network dimensions could be potentially linked to racial identifications in the future (Elmer, Boda, and Stadtfeld 2017;Vörös and Snijders 2017). Of these, negative ties could be particularly important because of their strong influence on groups (Huitsing et al 2012;Boda and Néray 2015;Pál et al 2016) (though interestingly, initial results did not show significant effects for negative ties on ethnic classifications).…”

Section: Discussionmentioning

confidence: 98%

Social Influence on Observed Race

Boda¹

2018

SocScience

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This article introduces a novel theoretical approach for understanding racial fluidity, emphasizing the social embeddedness of racial classifications. We propose that social ties affect racial perceptions through within-group micromechanisms, resulting in discrepancies between racial self-identifications and race as classified by others. We demonstrate this empirically on data from 12 Hungarian high school classes with one minority group (the Roma) using stochastic actor-oriented models for the analysis of social network panel data. We find strong evidence for social influence: individuals tend to accept their peers' judgement about another student's racial category; opinions of friends have a larger effect than those of nonfriends. Perceived social position also matters: those well-accepted among majority-race peers are likely to be classified as majority students themselves. We argue that similar analyses in other social contexts shall lead to a better understanding of race and interracial processes.

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Section: Discussionmentioning

confidence: 98%

Social Influence on Observed Race

Boda¹

2018

SocScience

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“…Further investigations are necessary to improve the model used for one plant category, for example, by declaring the two other networks as covariates of the model. Another alternative could be to use a bivariate ERGM to estimate the level of interaction between two networks through the entrainment effect (Huitsing et al 2012). To explore further how plant circulation is embedded within other social networks, it would be relevant to study, simultaneously and in interaction, the circulation of objects of different natures (e.g., musical instruments or other artifacts) and different networks of relationships in which these objects may circulate (kinship, advice, neighbor, and friendship networks), all in a multiplex analysis.…”

Section: Specificities Of Plant Circulation Networkmentioning

confidence: 99%

Effects of farmer social status and plant biocultural value on seed circulation networks in Vanuatu

Thomas¹,

Caillon²

2016

E&S

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ABSTRACT. Seed circulation among farmers, which is embedded in composite social networks, is a key process in the dynamics of seed systems that shape crop diversity. We analyzed the daily circulation of biological objects, i.e., cultivated plants (31 species, 284 landraces), within a community of first-generation migrants (16 households, 30 persons) living on the island of Vanua Lava in the South Pacific archipelago nation of Vanuatu. By combining participant observation, ethnobiological inventories, and social network analysis, we investigated how farmer social status and plant biocultural value affect plant circulation. Plant biocultural value was estimated by referring to their local classification according to uses, cultivation practices, growing environments, and biological properties. An aggregate plant circulation network (577 events) and three subnetworks (i.e., for starchy, side dish, or snack food categories) sharing the same 30 nodes were analyzed using exponential random graph models. Evidence that farmer social status influences the patterns of plant circulation was found through the distribution of structural parameters of the network, including: dyadic reciprocity; in-degree, out-degree, and their correlation; triadic cycling; and transitivity. At the scale of the aggregate network, direct or indirect reciprocity was not observed. Instead, a high out-degree (i.e., being a more frequent giver) and a negative correlation between in-degree and out-degree both confer prestige and reinforce hierarchy. These results suggest that some of the social dynamics of the Melanesian-type Big Man political system may persist, even though the system itself no longer exists in traditional form. Moreover, based on our comparative analysis of the three subnetworks, farmer social status appears to influence greatly the circulation of plants with high biocultural value while having little influence on plants with low biocultural value. Farmer social status and plant biocultural value (following their local classification) are important factors for understanding the social rules shaping seed circulation.

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“…In general, studies on negative relationships are rare, especially among educators, likely because of the difficulty of collecting empirical data to examine such relationships. In classroom research, a few studies investigating bully-victim relationships (e.g., Huitsing et al 2012;Veenstra et al 2007;Zijlstra et al 2008) shed light on the social structure of such negative relationships. Recently, organizational research has started to examine negative relationships in the workplace.…”

Section: Social-network Theory and Negative Tiesmentioning

confidence: 99%

“…Reciprocal negative ties.-Studies in organizations and classrooms indicate that negative relationships, in comparison to positive relationships, are more likely to be reciprocated, meaning that if one person dislikes another, this dislike is likely to be mutual (Huitsing et al 2012;Labianca and Brass 2006;Yap and Harrigan 2015). These reciprocated negative ties are likely to create additional social liabilities, as they represent at best a gap in the network or at worst an ongoing conflict that can diffuse across a system and influence other actors.…”

Section: Social-network Theory and Negative Tiesmentioning

confidence: 99%