Forecasting news across Twitter

A new research project tracks the spread of news stories across Twitter, claiming to predict how this will occur.  Fascinating idea.

The method involves analyzing a story’s content and context:

  • The news source that generates and posts the article (derived over time; a mix of traditional journalism and blogs, apparently)
  •  The category of news this article falls under (derived from Feedzilla)
  •  The subjectivity of the language in the article (interesting tools for this)
  •  Named entities mentioned in the article (a known place, person, or organization)

The category breakdown interested me.  From an SEO-ish perspective, what types of stories circulate best in the Twittersphere?

Interestingly, Huberman et al found that these categories weren’t actually that useful.  The biggest predictor?

Overall, we discovered that one of the most important predictors of popularity was the source of the article. This is in agreement with the intuition that readers are likely to be influenced by the news source that disseminates the article.

Consider it a sign that information fluency is rising.

(thanks to Mike Carpenter)

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