According to a new study, download patterns for catchy songs resemble the curve drawn by epidemiologists to chart the spread of infectious diseases.
Mathematicians, including Dora P. Rosati of McMaster University in Canada, say that the social processes underlying the popularity of songs are similar to those that transmit infectious diseases from one host to another.
They say the findings, published in the journal Proceedings of the Royal Society A: Mathematical and Physical Sciences, could help create a better tool for studying song popularity.
In the research, scientists analyzed data from online music streaming service MixRadio, which included information on downloading songs via Nokia cell phones in the UK from 2007 to 2014.
They then assessed the potential of what is known as the SIR (susceptible-infectious-recovered) model – which is used by epidemiologists to chart the spread of diseases – which included capturing download patterns of popular songs. Is. bad Romance by Lady Gaga, and a team by Ed Sheeran.
When an infectious disease, such as COVID-19, enters a population, it is initially transmitted from person to person through social contact.
The prevalence of the disease eventually peaks, after which the number of susceptible people in the population declines and/or the spread of the disease decreases as infected individuals recover.
Epidemiologists have applied this understanding to predict the spread of diseases using the SIR mathematical model.
Similarly, when a new hit song is released, scientists say it rapidly “spreads” through a population, “from person to person and through various media, eventually reaching some peak popularity.” reaches and then falls short in appeal.”
“At the end of a disease epidemic, a large proportion of the population will have been infected with the disease, whereas at the end of a period of extreme popularity of a hit song, a large proportion of the population will recognize that song,” the researchers note in the study. , to make a comparison between the two processes.
Mathematicians found that the SIR model describes song download trends for popular songs well, and can be a good representation of the processes driving song popularity.
The analysis also revealed that the download pattern differed for songs based on their genre.
For example, download patterns of electronica songs in music databases followed a shorter time period than pop songs, according to the study.
Scientists say that electronica-style songs gain popularity faster than other genres, and “burn through their susceptible populations more quickly.”
The study defined a susceptible population as a group of individuals who could download a song when exposed to it.
Comparing the way the two genres share and download songs, Mathematica speculates that electronica fans may be more proficient or more proactive in broadcasting their favorite songs.
“The social network of electronica fans may be more strongly connected than the fan communities of other music genres such as pop. Electronica fans may be more passionate about their favorite songs and bands than pop fans, and therefore their Lets talk more about and promote favorite songs,” he wrote in the research.
“Popular songs often described as ‘viral’ or ‘catchy’ as if they can ‘infect’ people, perhaps this description is more appropriate than previously thought,” he said.
The researchers believe that the SIR model can be used to capture the underlying “song transmission mechanism or the infectious process that drives song popularity.”
To validate the findings, the scientists call for future studies with the same type of analysis on a different song dataset.
The study states, “Although our results suggest that the model describes the song download dynamics well, its structure is too low to represent all the nuances of a song spreading through a population. ”
Scientists say that studying song download patterns using more subtle disease transmission models, which contain more biological insights, could shed better light on the important processes driving “song transmission.”
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