Political scientists have long studied the news cycle, tracking which people and topics drive coverage and for how long. But the sheer volume of news outlets made it hard to quantify their results.

Researchers at Cornell University are trying to get a quantitative handle on how news stories proliferate. Computer scientist Jon ­Kleinberg reasoned that instead of trying to sort items from blogs and news sites into arbitrary categories, he could home in on quotes to identify their topics computationally. But references to a quote might extract different phrases from it, change its tense, or paraphrase it, resulting in dozens of different versions. So Kleinberg and his colleagues developed algorithms that determine family resemblances between strings of words in different articles.