Aggregation and the Future of Local NewsHunting through thousands of local blogs for quality tidbits of regional interest is too time-consuming for overtaxed, understaffed news teams. Why not rely on clever algorithms, much the way Facebook manages social news? That logic has inspired news giants
to place big bets this past year on aggregation. MSNBC bought automated news site EveryBlock.com, AOL picked up local blog network Patch.com and CNN invested in Outside.in. The next target might be Fwix.com, an automated newswire with a silly name but serious ambition.
By Jeremy Caplan, Wall Street Journal
Led by CEO Darian Shirazi, 23, Fwix signed a recent deal to provide aggregated local news for the New York Times Company. Fwix, founded in October 2008, sorts through about 200,000 pieces of news every day, analyzing and filtering stories from tens of thousands of local sources.Fwix's aggregated news flows to about 14 million readers a month on its own site and those of its news partners. Mr. Shirazi spoke to Digits about the future of local news and aggregation.
What role do you see automated aggregation services playing in the news ecosystem?
The true value to news in the future will be filtration of content and using technology to ensure that published news speaks well to user preferences and reader expectations. There aren't enough editors in the world and there isn't enough money to pay hundreds of editors to filter the growing online content universe.
How does news aggregation impact local newspapers?
I think that the problem with the local newspaper is that it focuses too much on "generally applicable" stories. When I say 'generally applicable,' I'm referring to crime articles or republished AP content. Local newspapers have lost their touch as the medium for communicating the metropolitan Zeitgeist - likely due to declining revenue and, therefore, smaller staff.
Many people think the demise of the local newspaper is because of the Internet or Google; the truth is that Craigslist and eBay have done the most damage to the economics of the industry (ads and classified ads). The challenge is now reducing costs of getting content and filtering the content for users. I think that aggregated news is definitely information overload, and that's why we've focused on building the filters and normalization that makes this aggregated news more readable, useful and valuable.