Unraveling the Impact of Visual Cues in Online Portraits on Workers’ Employability in Digital Labor Markets

Yuting Jiang, Matti Rossi, Virpi Kristiina Tuunainen, Zhao Cai, Chee-Wee Tan

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Abstract

Online portraits constitute a pervasive and critical signal in digital labor markets in that workers can boost their employability by manipulating select visual cues embedded in these portraits. Consequently, we attempt to unravel how visual cues embedded in workers’ portraits within digital labor markets can collectively influence constituent dimensions of employability. Notably, we advance a non-verbal cues classification model that differentiates among demographic, physical appearance, image quality, and non-verbal behavioral cues as focal determinants affecting one’s employment status, the number of job offers received, and rehiring probability. Employing computer vision and deep learning algorithmic techniques to analyze the online portraits and personal information of 53,950 workers on Upwork.com, we demonstrate that visual cues embedded in profile portraits exert a significant effect on workers’ employability in digital labor markets.
OriginalsprogEngelsk
TitelProceedings of the 57th Hawaii International Conference on System Sciences
RedaktørerTung Bui
Antal sider10
UdgivelsesstedHonolulu
ForlagHawaii International Conference on System Sciences (HICSS)
Publikationsdato2024
Sider693-702
ISBN (Trykt)9780998133171
DOI
StatusUdgivet - 2024
BegivenhedThe 57th Hawaii International Conference on System Sciences. HICSS 2024 - Hilton Hawaiian Village Waikiki Beach Resort, Honolulu, USA
Varighed: 3 jan. 20246 jan. 2024
Konferencens nummer: 57
https://hicss.hawaii.edu/

Konference

KonferenceThe 57th Hawaii International Conference on System Sciences. HICSS 2024
Nummer57
LokationHilton Hawaiian Village Waikiki Beach Resort
Land/OmrådeUSA
ByHonolulu
Periode03/01/202406/01/2024
Internetadresse
NavnProceedings of the Annual Hawaii International Conference on System Sciences
ISSN1060-3425

Emneord

  • Visual cues
  • Non-verbal classification model
  • Deep learning
  • Digital labor market

Citationsformater