Predicting popular news on Twitter

Bernardo Huberman and colleagues at HP’s Social Computing Lab have come up with four factors that make news stories popular on Twitter.

The group examined the content of news stories during a week in August last year, scoring each article based on four criteria: the news source that generates and posts the article; the category of news; the subjectivity of the language; and the people and things named in the article.

Then they measured the way news stories spread across Twitter to see which became popular and how quickly. They used this to work out how an article’s score in each criteria is linked to its popularity. “Our experiments show that it is possible to estimate ranges of popularity with an overall accuracy of 84% considering only content features.”

Will this change the way articles are written and edited?

Read the full Technology Review article here.