Nguyen, QT and Naguib, RNG and Loo, M (2021) Towards Emotional Intelligence: Analysis of Static Facial Features in LinkedIn Profile Pictures. In: 2nd IEEE IAS International Conference on Computational Performance Evaluation (ComPE-2021), 1-3 December 2021, North-Eastern Hill University (NEHU), Shillong, Meghalaya, India. (Accepted for Publication)
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Abstract
In an attempt to distil information conveyed by LinkedIn users’ pictures, in addition to the usual information provided in their profiles, we explored a large public dataset of 10,610 Australian LinkedIn users. The dataset contained in excess of 50 parameters, of which 22 were dedicated to picture features. The study confirmed that K-means clustering and Principal Component Analysis (PCA) are viable techniques for the classification of users, based on facial feature extraction and analysis. Furthermore, the study demonstrated that reduction in feature dimensionality, using PCA, yielded a significant improvement in computational time and resource consumption.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Keywords: | K-means clustering, Principal Component Analysis, Picture classification, Facial features, Social media profiles. |
| Faculty / Department: | Faculty of Human and Digital Sciences > Mathematics and Computer Science |
| Depositing User: | Raouf Naguib |
| Date Deposited: | 05 Nov 2021 13:42 |
| Last Modified: | 04 Dec 2021 01:15 |
| URI: | https://hira.hope.ac.uk/id/eprint/3399 |
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