his.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Social network analysis to influence career development
UAE University, Al Ain, United Arab Emirates.
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Distribuerade realtidssystem (DRTS), Distributed Real-Time Systems)ORCID iD: 0000-0002-7312-9089
2018 (English)In: Journal of Ambient Intelligence and Humanized Computing, ISSN 1868-5137, E-ISSN 1868-5145, Vol. 9, no 3, p. 601-616Article in journal (Refereed) Published
Abstract [en]

Social network analysis techniques have shown a potential for influencing gradu-ates to meet industry needs. In this paper, we propose a social-web driven solutions to bridge formal education and industry needs. The proposed career development frame-work utilizes social network analytics, influence diffusion algorithms and persuasive technology models along three phases: (1) career readiness to measure and visualize the general cognitive dispositions required for a successful career in the 21st Century, (2) career prediction to persuade future graduates into a desired career path by clustering learners whose career prospects are deemed similar, into a community of practice; and (3) career development to drive growth within a social network structure where social network analytics and persuasive techniques are applied to incite the adoption of desired career behaviors. The process starts by discovering behavioral features to create a cognitive profile and diagnose individual deficiencies. Then, we develop a fuzzy clustering algorithm that predicts similar patterns with controlled constraint-violations to construct a social structure for collaborative cognitive attainment. This social framework facilitates the deployment of novel influence diffusion approaches, whereby we propose a reciprocal-weighted similarity function and a triadic clo-sure approach. In doing so, we investigate contemporary social network analytics to maximize influence diffusion across a synthesized social network. The outcome of this social computing approach leads to a persuasive model that supports behavioral changes and developments. The performance results obtained from both analytical and experi-mental evaluations validate our data-driven strategy for persuasive behavioral change.

Place, publisher, year, edition, pages
Springer, 2018. Vol. 9, no 3, p. 601-616
Keywords [en]
Social web, Community of practice, Big data, Learning analytics, Computational science, Fuzzy logic
National Category
Computer and Information Sciences
Research subject
Distributed Real-Time Systems; INF301 Data Science
Identifiers
URN: urn:nbn:se:his:diva-13398DOI: 10.1007/s12652-017-0457-9ISI: 000434911600011Scopus ID: 2-s2.0-85048261802OAI: oai:DiVA.org:his-13398DiVA, id: diva2:1075358
Available from: 2017-02-18 Created: 2017-02-18 Last updated: 2018-07-05Bibliographically approved

Open Access in DiVA

fulltext(3235 kB)3 downloads
File information
File name FULLTEXT03.pdfFile size 3235 kBChecksum SHA-512
6e93e34e2013d47022893159c86d24c5c5f52dbafee471b54f3e571acbabdebe2a12e6d590fe773905ca10506a6df219fe8d87d6e96b2d5a1260b20b0892be23
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopus

Authority records BETA

Atif, Yacine

Search in DiVA

By author/editor
Atif, Yacine
By organisation
School of InformaticsThe Informatics Research Centre
In the same journal
Journal of Ambient Intelligence and Humanized Computing
Computer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 34 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 539 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf