Estimating how infectious a tweet is from the first 50 re-tweets is the key to predicting whether a post will go viral or not, a study has found.
As online social networks and media continue to grow, so has the importance of understanding how they influence our thoughts and opinions, said researchers from Beihang University in China.
Being able to predict the spread of social contagions is considered a key goal for those social information networks, according to the study published in the journal PLOS ONE .
Researchers used about one month of Twitter data — comprising over 12 million tweets and more than 1.5 million re-tweets — and estimated each tweet’s infectivity based on the network dynamics of the first 50 re-tweets associated with it.
They incorporated the infectivity estimates into a model with a decay constant that captures the gradual decline in interest as online information ages.
Performance comparison
Using real data and simulations, the researchers tested the ability of the infectivity-based model to predict the virality of re-tweet cascades.
They compared its performance to that of the standard community model, which incorporates other predictive factors — such as social reinforcement and trapping effects that act to keep tweet cascades within small communities of connected users.
The researchers found that for both real Twitter data and simulated data, the infectivity model performed better than the community model, indicating that infectivity is a larger driving force in determining whether a tweet goes viral.
Comments
Comments have to be in English, and in full sentences. They cannot be abusive or personal. Please abide by our community guidelines for posting your comments.
We have migrated to a new commenting platform. If you are already a registered user of TheHindu Businessline and logged in, you may continue to engage with our articles. If you do not have an account please register and login to post comments. Users can access their older comments by logging into their accounts on Vuukle.