SCCD: Social Capital-Driven Career Development Framework
|Title:||SCCD: Social Capital-Driven Career Development Framework||Authors:||Ghaffar, Faisal; Buda, Teodora Sandra; Assem, Haytham; Afsharinejad, Armita; Hurley, Neil J.||Permanent link:||http://hdl.handle.net/10197/11407||Date:||31-Aug-2018||Online since:||2020-07-03T15:55:03Z||Abstract:||Sociological theories of career success provide fundamental principles for the analysis of social networks to identify patterns that facilitate career development. Structural Hole Theory argues that certain network structures provide advantages to individuals by facilitating them to access unique information from parts of the network. The network structural advantages of social networks in workplace settings have not been studied enough for the purpose of employees career development. In this paper, we address this challenge by proposing a Social Capital-Driven Career Development framework which leverages enterprise collaboration activity streams to assess employees social capital across organizational hierarchy levels. We demonstrate that our framework can enable employees to reflect on their social network structure from the prospective of information benefits for progressing their career from one hierarchy level to the immediate next level in their respective business units.||Funding Details:||European Commission Horizon 2020
Science Foundation Ireland
|metadata.dc.description.othersponsorship:||Insight Research Centre||Type of material:||Conference Publication||Publisher:||IEEE||Copyright (published version):||2018 European Union||Keywords:||Recommender systems; Social network services; Collaboration; Phase measurement; Blogs; Career development; Engineering profession; Organizations||DOI:||10.1109/ASONAM.2018.8508320||Other versions:||http://asonam.cpsc.ucalgary.ca/2018/||Language:||en||Status of Item:||Peer reviewed||Conference Details:||The 2018/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2018), Barcelona, Spain, 28-31 August 2018||ISBN:||978-1-5386-6051-5|
|Appears in Collections:||Insight Research Collection|
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