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| Andrea Capiluppi, Alexander Serebrenik, Leif Singer, "Assessing Technical Candidates on the Social Web," IEEE Software, vol. 30, no. 1, pp. 45-51, Jan.-Feb., 2013. | |||
| BibTex | x | ||
| @article{ 10.1109/MS.2012.169, author = {Andrea Capiluppi and Alexander Serebrenik and Leif Singer}, title = {Assessing Technical Candidates on the Social Web}, journal ={IEEE Software}, volume = {30}, number = {1}, issn = {0740-7459}, year = {2013}, pages = {45-51}, doi = {http://doi.ieeecomputersociety.org/10.1109/MS.2012.169}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - MGZN JO - IEEE Software TI - Assessing Technical Candidates on the Social Web IS - 1 SN - 0740-7459 SP45 EP51 EPD - 45-51 A1 - Andrea Capiluppi, A1 - Alexander Serebrenik, A1 - Leif Singer, PY - 2013 KW - Social network services KW - Media KW - Internet KW - Web and internet services KW - LinkedIn KW - Recruitment KW - Professional aspects KW - knowledge management KW - collaborative computing KW - group and organization interfaces KW - information interfaces and representation KW - HCI KW - knowledge retrieval VL - 30 JA - IEEE Software ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MS.2012.169
The Social Web provides comprehensive and publicly available information about software developers, identifying them as contributors to open source projects, experts at maintaining ties on social network sites, or active participants on knowledge-sharing sites. These signals, when aggregated and summarized, could be used to define potential candidates' individual profiles: potential employers could qualitatively evaluate job seekers, even those lacking a formal degree or changing their career path, by assessing candidates' online contributions. At the same time, developers are aware of the Web's public nature and the possible uses of published information when they determine what to share with the world. Some might even try to manipulate public signals of technical qualifications, soft skills, and reputation in their favor. Assessing candidates on the Web for technical positions presents challenges to recruiters, the most serious being the interpretation of the provided signals. An in-depth discussion proposes guidelines for software engineers and recruiters to help recruiters interpret the value and trouble with the signals and metrics they use to assess a candidate's characteristics and skills.
Index Terms:
Social network services,Media,Internet,Web and internet services,LinkedIn,Recruitment,Professional aspects,knowledge management,collaborative computing,group and organization interfaces,information interfaces and representation,HCI,knowledge retrieval
Citation:
Andrea Capiluppi, Alexander Serebrenik, Leif Singer, "Assessing Technical Candidates on the Social Web," IEEE Software, vol. 30, no. 1, pp. 45-51, Jan.-Feb. 2013, doi:10.1109/MS.2012.169
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