Actually, aggregation has a long, proud and ethical history in journalism. If you’re an old-school journalist, don’t think Huffington Post or Drudge when you think about aggregation; think AP. The Associated Press is primarily an aggregation service*, except that it its members pay huge fees for the privilege of being aggregated (and for receiving content aggregated from other members).
The New York Times and Washington Post also have long histories of aggregation. In my years at various Midwestern newspapers, we reported big local and regional stories that attracted the attention of the Times, Post and other national news organizations. Facts we had reported first invariably turned up in the Times and Post stories without attribution or with vague attribution such as “local media reports.” I don’t say that critically. When I was a reporter and editor at various Midwestern newspapers, we did the same thing with facts we aggregated from smaller newspapers as we did regional versions of their local stories.
Predicting the Spread of News
Researchers are analyzing if its possible to predict how widely news items will spread before publishing and promoting them via social networks.
By analyzing past performance of popular Twitter posts, the researchers from UCLA and HP Labs believe they can predict ranges of popularity on Twitter with 84% accuracy.
Via Technology Review:
[Bernardo Huberman] wants to know whether their is something about the news stories themselves that determine their popularity. In other words, he’s looking for factors that determine how popular a news story will be before it is even published.
To find out, Huberman and his colleagues examined the content of news stories during a single week in August last year as measured by the news feed aggregator Feedzilla. They scored 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.
They then measured the way these news stories spread across the Twitter network to see which became popular and how quickly. They used this to work out how an article’s score in each criterion is linked to its eventual popularity.
Technology Review rightfully points out that this could have a profound effect on how newsrooms assign and schedule their editorial. It also suggests that we could have “social checkers” in our word processing apps and CMS’s that work similarly to spell checkers. The social checker would help predict how popular our stories will become.
An interesting metric even if it ignores the simple fact that often the most important stories aren’t the ones that reach the most eyeballs.
Study: The Pulse of News in Social Media: Forecasting Popularity, via arxiv (PDF).
How to make money from digital news
There is still cash to be made from journalism when the presses stop rolling
Fonte: Guardian
What newsrooms should learn from Kodak
So Kodak, the company that invented amateur photography in the 19th century and invented digital photography in the 20th, is on the ropes. There are obvious lessons for newspapers and newsrooms. Here are a few of them.
Your business isn’t what you think it is. Kodak at its peak looked like a photography company, but it was really a giant chemical manufacturing company. Digital tech rendered the entire chemical photography business irrelevant. By comparison, newspapers looked like news and information companies, but they were really expensive commercial advertisement printing and delivery systems. If you have borrowed heavily to build and maintain capital-intensive processes that are suddenly rendered irrelevant, you’re in deep trouble no matter how smart you are and no matter what you do. Printing isn’t yet irrelevant, but it’s trending that way. This is not to the time to invest in a new three-around compact press line.
Fonte: yelvington.com
The key strategic opportunity for news sites is relationships — deeper, more valuable relationships with more (but not too many) people. Engagement.
Why not a reverse meter? Jeff Jarvis
Fonte: buzzmachine.com
