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1.
Health Commun ; 37(14): 1724-1730, 2022 12.
Article in English | MEDLINE | ID: mdl-33855925

ABSTRACT

The role of social support in the online setting is explored in this study. For this purpose, the posts of infertility treatment patients participating in an infertility treatment online support group between 2002 and 2016 were retrieved. Members who contributed at least 100 words were divided into two groups according to the treatment outcome they reported (pregnancy). The association between the length of group membership, type of support provided, intensity of interaction, active support seeking, overall sentiment and the amount of sadness, anxiety and anger words and the treatment outcome was examined. The findings suggest that online social, in particular emotional, support acts as a buffer between the stressor and the treatment outcome. The expression of anger and initiating of communication by new members diminish this relationship.


Subject(s)
Infertility , Social Support , Pregnancy , Female , Humans , Self-Help Groups , Anxiety , Counseling , Infertility/therapy
2.
PLoS One ; 16(2): e0246660, 2021.
Article in English | MEDLINE | ID: mdl-33591999

ABSTRACT

Understanding the patterns and underlying mechanisms that come into play when employees exchange their knowledge is crucial for their work performance and professional development. Although much is known about the relationship between certain global network properties of knowledge-flow networks and work performance, less is known about the emergence of specific global network structures of knowledge flow. The paper therefore aims to identify a global network structure in blockmodel terms within an empirical knowledge-flow network and discuss whether the selected local network mechanisms are able to drive the network towards the chosen global network structure. Existing studies of knowledge-flow networks are relied on to determine the local network mechanisms. Agent-based modelling shows the selected local network mechanisms are able to drive the network towards the assumed hierarchical global structure.


Subject(s)
Knowledge Management/statistics & numerical data , Work Performance/statistics & numerical data , Algorithms , Humans , Knowledge , Models, Theoretical , Work Performance/trends
3.
PLoS One ; 15(1): e0226801, 2020.
Article in English | MEDLINE | ID: mdl-31940323

ABSTRACT

Researchers have extensively studied the social mechanisms that drive the formation of networks observed among preschool children. However, less attention has been given to global network structures in terms of blockmodels. A blockmodel is a network where the nodes are groups of equivalent units (according to links to others) from a studied network. It is already shown that mutuality, popularity, assortativity, and different types of transitivity mechanisms can lead the global network structure to the proposed asymmetric core-cohesive blockmodel. Yet, they did not provide any evidence that such a global network structure actually appears in any empirical data. In this paper, the symmetric version of the core-cohesive blockmodel type is proposed. This blockmodel type consists of three or more groups of units. The units from each group are internally well linked to each other while those from different groups are not linked to each other. This is true for all groups, except one in which the units have mutual links to all other units in the network. In this study, it is shown that the proposed blockmodel type appears in empirical interactional networks collected among preschool children. Monte Carlo simulations confirm that the most often studied social network mechanisms can lead the global network structure to the proposed symmetric blockmodel type. The units' attributes are not considered in this study.


Subject(s)
Models, Theoretical , Social Networking , Algorithms , Child, Preschool , Humans , Interpersonal Relations , Social Behavior
4.
PLoS One ; 13(5): e0197514, 2018.
Article in English | MEDLINE | ID: mdl-29847563

ABSTRACT

This paper addresses the question of whether one can generate networks with a given global structure (defined by selected blockmodels, i.e., cohesive, core-periphery, hierarchical, and transitivity), considering only different types of triads. Two methods are used to generate networks: (i) the newly proposed method of relocating links; and (ii) the Monte Carlo Multi Chain algorithm implemented in the ergm package in R. Most of the selected blockmodel types can be generated by considering all types of triads. The selection of only a subset of triads can improve the generated networks' blockmodel structure. Yet, in the case of a hierarchical blockmodel without complete blocks on the diagonal, additional local structures are needed to achieve the desired global structure of generated networks. This shows that blockmodels can emerge based only on local processes that do not take attributes into account.


Subject(s)
Algorithms , Monte Carlo Method , Social Networking , Computer Simulation , Humans , Markov Chains , Models, Theoretical
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