Inferring social media users’ demographics from profile pictures: A Face++ analysis on Twitter users
Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
12-2017
Abstract
In this research, we evaluate the applicability of using facial recognition of social media account profile pictures to infer the demographic attributes of gender, race, and age of the account owners leveraging a commercial and well-known image service, specifically Face++. Our goal is to determine the feasibility of this approach for actual system implementation. Using a dataset of approximately 10,000 Twitter profile pictures, we use Face++ to classify this set of images for gender, race, and age. We determine that about 30% of these profile pictures contain identifiable images of people using the current state-of-the-art automated means. We then employ human evaluations to manually tag both the set of images that were determined to contain faces and the set that was determined not to contain faces, comparing the results to Face++. Of the thirty percent that Face++ identified as containing a face, about 80% are more likely than not the account holder based on our manual classification, with a variety of issues in the remaining 20%. Of the images that Face++ was unable to detect a face, we isolate a variety of likely issues preventing this detection, when a face actually appeared in the image. Overall, we find the applicability of automatic facial recognition to infer demographics for system development to be problematic, despite the reported high accuracy achieved for image test collections
Keywords
Face++, Twitter, demographic inference, social media, demographics, user attributes, personas
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing | Social Media
Research Areas
Data Science and Engineering
Publication
Proceedings of the International Conference on Electronic Business (ICEB) 2017: December 4-8, Dubai
First Page
140
Last Page
145
Publisher
ICEB
City or Country
Dubai, UAE
Citation
1
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://aisel.aisnet.org/iceb2017/22/
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons, Social Media Commons