Future Journalists, Pounding the Pavement
The following was written by a robot:

Newt Gingrich received the largest increase in Tweets about him today. Twitter activity associated with the candidate has shot up since yesterday, with most users tweeting about taxes and character issues. Newt Gingrich has been consistently popular on Twitter, as he has been the top riser on the site for the last four days. Conversely, the number of tweets about Ron Paul has dropped in the past 24 hours. Another traffic loser was Rick Santorum, who has also seen tweets about him fall off a bit.
While the overall tone of the Gingrich tweets is positive, public opinion regarding the candidate and character issues is trending negatively. In particular, @MommaVickers says, “Someone needs to put The Blood Arm’s ‘Suspicious Character’ to a photo montage of Newt Gingrich. #pimp”.

Stilted and inelegant to be sure, the computer generated story was created by Narrative Science, an Illinois-based startup, that’s combining machine learning, data analysis and artificial intelligence to produce short and long form articles from data heavy industries such as real estate, finance, sports and polling.
For example, Narrative Science technology creates computer generated sports recaps for the Big Ten Network, a joint venture between the Big Ten Conference and Fox Networks.
As the New York Times explained last fall:

The Narrative Science software can make inferences based on the historical data it collects and the sequence and outcomes of past games. To generate story “angles,” explains Mr. Hammond of Narrative Science, the software learns concepts for articles like “individual effort,” “team effort,” “come from behind,” “back and forth,” “season high,” “player’s streak” and “rankings for team.” Then the software decides what element is most important for that game, and it becomes the lead of the article, he said. The data also determines vocabulary selection. A lopsided score may well be termed a “rout” rather than a “win.”

Glass half empty: journalists will be automated out of their jobs.
Glass half full: journalists will be freed from writing drudgey news summaries and can focus on more significant work.
Image: via Senor Roboto (yes, I smiled too).

Future Journalists, Pounding the Pavement

The following was written by a robot:

Newt Gingrich received the largest increase in Tweets about him today. Twitter activity associated with the candidate has shot up since yesterday, with most users tweeting about taxes and character issues. Newt Gingrich has been consistently popular on Twitter, as he has been the top riser on the site for the last four days. Conversely, the number of tweets about Ron Paul has dropped in the past 24 hours. Another traffic loser was Rick Santorum, who has also seen tweets about him fall off a bit.

While the overall tone of the Gingrich tweets is positive, public opinion regarding the candidate and character issues is trending negatively. In particular, @MommaVickers says, “Someone needs to put The Blood Arm’s ‘Suspicious Character’ to a photo montage of Newt Gingrich. #pimp”.

Stilted and inelegant to be sure, the computer generated story was created by Narrative Science, an Illinois-based startup, that’s combining machine learning, data analysis and artificial intelligence to produce short and long form articles from data heavy industries such as real estate, finance, sports and polling.

For example, Narrative Science technology creates computer generated sports recaps for the Big Ten Network, a joint venture between the Big Ten Conference and Fox Networks.

As the New York Times explained last fall:

The Narrative Science software can make inferences based on the historical data it collects and the sequence and outcomes of past games. To generate story “angles,” explains Mr. Hammond of Narrative Science, the software learns concepts for articles like “individual effort,” “team effort,” “come from behind,” “back and forth,” “season high,” “player’s streak” and “rankings for team.” Then the software decides what element is most important for that game, and it becomes the lead of the article, he said. The data also determines vocabulary selection. A lopsided score may well be termed a “rout” rather than a “win.”

Glass half empty: journalists will be automated out of their jobs.

Glass half full: journalists will be freed from writing drudgey news summaries and can focus on more significant work.

Image: via Senor Roboto (yes, I smiled too).

  1. lifeandcode reblogged this from futurejournalismproject and added:
    Life and Code: the tumblr for journalists who want to learn to code, dive into data journalism, and more.
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    picture! futurejournalismproject:
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    FUCK YOU GOD DAMN MOTHERFUCKING SCIENTISTS SCREWING JOURNALISTS OUT OF THEIR JOBS. FUCKING FUCK.
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