Mathematics and Computer Science

Romantic Fit Based on Sense of Smell Similarity (No. T4-1784)

Lead Researcher: Prof. Noam Sobel


Romantic relationships have major impact on our social, emotional and physical wellbeing. Despite this overwhelming importance, we have only limited understanding of the rules and mechanisms that are at the heart of good relationships. Popular notion holds that increased similarity between relationship partners is an omen for continued positive relationship quality, although studies of similarity in personality and attitude-measures failed to support this notion. Researchers have found that similarity in emotional characteristics may be more relevant to relationship quality. The sensory system that is most intimately linked to emotion is olfaction. Given this powerful link, Prof. Sobel and his olfaction research group hypothesize that individuals with similar olfactory perception would have good romantic relationships.
The new research observed a remarkably powerful association whereby couples who smell the world in the same way have good romantic relationships, i.e., this one measure explained ~50% of the variance in relationship quality. Thus, olfactory perception, which opens a unique window into the emotional brain, informs us that genuine similarity in primal, non-verbal essence is a component of successful romantic relationships.


·         Online matchmaking platform
·         Scent-marketing


  • High-accuracy prediction of romantic fit and personality traits

  • Straight-forward evaluation method and user interface operation
  • Technology's Essence

    The “SmellSpace” online platform generates individual smell-based identity that can predict one’s personality and smell-based matching score: https://smellspace.com/
    The method of perceptual fingerprinting includes:
    ·      Each user smells the same odors set
    ·      The user rates the odors using verbal descriptors.
    ·      The perceived similarity of all possible pairs of odors is calculated and the pairwise similarities form a matrix.
    ·      Finally, the matrices are correlated across individuals.