Identification of Social Tension in Organizational Networks

Collingsworth, Ben; Menezes, Ronaldo

doi:10.1007/978-3-642-01206-8_18

Cited by 6 publications

(4 citation statements)

References 9 publications

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“…Prior research has indicated that RNs can be commonly found in knowledge-intensive industries [34]. Research on mining e-mail networks indicates the presence of multiple cliques (as in CNs) in some organizations [14,58]. SNs are extremely common [21] and may also be appropriate in IT-intensive work environments [34,54].…”

Section: Social Networking and Knowledge Sharing In Work Processesmentioning

confidence: 99%

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A Benchmarking Model for Management of Knowledge-Intensive Service Delivery Networks

Dong

Johar

Kumar

2011

Journal of Management Information Systems

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others. He has advised the U.S. Department of Energy and organizations in the private sector on the evaluation of R&D projects and IT portfolios.abStract: Effective management of information technology (IT) and IT-enabled services is becoming increasingly important due to the growing complexity of their context. These services are often delivered by employees who work at widely dispersed locations and interact with each other to constitute knowledge-intensive service delivery networks (KISDNs). This paper contributes to the effective design and management of KISDNs by presenting a mixed-integer programming model that integrates disparate streams of research. This model facilitates analysis and managerial benchmarking of KISDN performance. It captures how the performance of such networks depends on Downloaded by [UQ Library] at 01

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Section: Social Networking and Knowledge Sharing In Work Processesmentioning

confidence: 99%

“…Since RNs invoke the most efficient help-sharing behavior, RNs are less sensitive to increase in the cost of providing help, compared to SNs and CNs, in that order. 14 …”

Section: Impact Of Cost Of Providing Help On Relative Network Performmentioning

confidence: 99%

A Benchmarking Model for Management of Knowledge-Intensive Service Delivery Networks

Dong

Johar

Kumar

2011

Journal of Management Information Systems

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“…There are several papers that review the evolution of different types of real networks [27]. Other works utilize communication patterns in the dataset Enron email to: detect social tensions [11]; discover structures within the organization [10]; identify the most relevant actors in the network over time [44]. A more detailed work studied more than 100 real-world networks to reveal clusters or communities, the authors note that large networks have a very different structure compared to the small-world networks [28].…”

Section: Fig 2 Distribution Degrees Examplementioning

confidence: 99%

A traffic analysis attack to compute social network measures

Trujillo

Orozco

Villalba

et al. 2018

Multimed Tools Appl

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The development of digital media, the increasing use of social networks, the easier access to modern technological devices, is perturbing thousands of people in their public and private lives. People love posting their personal news without consider the risks involved. Privacy has never been more important. Privacy enhancing technologies research have attracted considerable international attention after the recent news against users personal data protection in social media websites like Facebook. It has been demonstrated that even when using an anonymous communication system, it is possible to reveal user's identities through intersection attacks or traffic analysis attacks. Combining a traffic analysis attack with Analysis Social Networks (SNA) techniques, an adversary can be able to obtain important data from the whole network, topological network structure, subset of social data, revealing communities and its interactions. The aim of this work is to demonstrate how intersection attacks can disclose structural properties and significant details from an anonymous social network composed of a university community.

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“…La première porte sur choix des médias de communication informelle, à savoir les échanges physiques. L'observation participante n'intègre donc pas tous les échanges dématérialisés : échanges téléphoniques, échanges d'e-mails (Collingsworth et Menezes, 2009). Un second biais tient à la présence d'un seul codeur qui ne peut tout voir à l'instant t. Mais ce biais est partiellement corrigé par la durée de l'observation : près de sept mois.…”

Section: Centralité Des Acteursunclassified

L'évolution d'un réseau social dans une réorganisation : « fluctuat nec mergitur »

Chanson¹,

Edouard²

2013

@Grh

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Identification of Social Tension in Organizational Networks

Cited by 6 publications

References 9 publications

A Benchmarking Model for Management of Knowledge-Intensive Service Delivery Networks

A Benchmarking Model for Management of Knowledge-Intensive Service Delivery Networks

A traffic analysis attack to compute social network measures

L'évolution d'un réseau social dans une réorganisation : « fluctuat nec mergitur »

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