Mathematical analysis of online perfume data reveals how the distinctive scent combinations discovered in several perfumes contribute to product popularity and consumer ratings. Every perfume is a unique combination of different factory components, oils, and chemical molecules, that collectively form a harmonious aroma. The fragrance of a perfume is often described using so-called notes, such as vanilla, and their combinations, such as musk along with jasmine, that is known as accords. By making an assumption that a given fragrance is popular largely due to its good fragrance, the analysts aim to understand what constitutes a popular fragrance. To attain this, the structure of perfumes and their constituent notes are studied based on the rules of a mathematical discipline generally known as advanced community evaluation.
To better understand how accords give to the success of perfumes, Vasiliauskaite and Evans applied complex network evaluation to online data on of 1,000 notes discovered in additional than 10,000 perfume products. The dataset included user ratings and information on the popularity of every perfume.
This evaluation revealed which notes and accords are used more often than one would expect by probability (are “over-represented”), that is preferred, and that is found in the highest-rated perfumes. The researchers discovered that the preferred notes and probably the most generally used accords don’t essentially correlate with the best fragrance rankings. As an example, the accord of jasmine and mint notes contributed considerably to larger rankings however was beneath-represented in the studied perfumes.
The researchers additionally decided which notes, when added to present accords, appeared to enhance accords essentially the most. They discovered that notes with high popularity, similar to musk and vanilla, tended to enhance accords the most, as did generically-named notes such as floral notes.