Abstract
It is common practice nowadays to use multiple social networks for different social roles. Although this, these networks assume differences in content type, communications and style of speech. If we intend to understand human behaviour as a key-feature for recommender systems, banking risk assessments or sociological researches, this is better to achieve using a combination of the data from different social media. In this paper, we propose a new approach for user profiles matching across social media based on publicly available users’ face photos and conduct an experimental study of its efficiency. Our approach is stable to changes in content and style for certain social media.
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Notes
- 1.
Code repository used - https://github.com/davidsandberg/facenet.
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Acknowledgments
This work financially supported by Ministry of Education and Science of the Russian Federation, Agreement #14.575.21.0165 (26/09/2017). Unique Identification RFMEFI57517X0165.
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Sokhin, T., Butakov, N., Nasonov, D. (2019). User Profiles Matching for Different Social Networks Based on Faces Identification. In: Pérez García, H., Sánchez González, L., Castejón Limas, M., Quintián Pardo, H., Corchado Rodríguez, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2019. Lecture Notes in Computer Science(), vol 11734. Springer, Cham. https://doi.org/10.1007/978-3-030-29859-3_47
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