Estimating how infectious a tweet is from the first 50 retweets is the key to predict whether a tweet will go viral or not, say researchers.
A tweet's virality is modulated most by its early spread rate and a gradual loss of interest over time.
A new "Infectivity" model developed by Li Weihua and team from Beihang University, China can accurately predict a tweet lifespan.
Although models developed in the field of infectious diseases have been used to describe the spread of ideas, studies have not used real data to estimate how infectious the information is, said the paper which appeared in the journal PLOS ONE.
To reach this conclusion, the researchers used about one month of Twitter data -- comprising over 12 million tweets and more than 1.5 million retweets -- and estimated each tweet's infectivity based on the network dynamics of the first 50 retweets associated with it.
They then incorporated the infectivity estimates into a model with a decay constant that captures the gradual decline in interest as online information ages.
"We propose a simulation model using Twitter data to show that infectivity, which reflects the intrinsic interestingness of an information cascade, can substantively improve the predictability of viral cascades," said researchers.