My own interest, of course, is in the behavioural, cognitive and information-processing aspects of this. Two particular questions are relevant:
- Rational people would apply an appropriate level of skepticism to crowdsourced news; weighting its credibility according to who the messenger is, by the number of times the same message has been recycled or retweeted, by the number of independent sources. But real people do not. Psychology tells us that we inevitably overweight a message the first time we hear it (anchoring), and by the degree to which it confirms our prior beliefs (confirmation bias). The role of a professional journalist, in part, is to check facts and give us appropriate caveats on how much we should believe what we're told.
How can this be done in the world of participatory journalism? Maybe we can develop automated tools of analysis which take into account behavioural biases. Twitter might be a powerful mechanism to do this: it lets us follow tweets back to their original source, find out how quickly they are being retweeted, and even estimate the potential bias of a message by the political opinions of those who are retweeting it. A tool like this would be a useful check on messages emerging from the citizen crowd.
I suspect we will also see the emergence of automated rapid-response - imagine if everyone retweeting an allegation about last week's News of the World scandal had received a message via twitter saying "there are two sides to this story - here's our version". An immediate response before people have fully formed a view would make negative opinions less likely to crystallise. At the very least it would have given the mass some pause. I'm not saying the popular consensus about the story is wrong, but News International would have benefited from better monitoring of that consensus and responding to it as it formed. (for that matter, could Twitter's long-awaited business model be partly based around detecting stories and allowing companies this kind of response?)
- The business model for news is likely to be determined in large part by behavioural or psychological factors. Behavioural issues are, arguably, the reason that the old economic model of news breaks down: readers do not try to rationally predict the utility from each news source and make a rational judgment about buying quality news; instead, they focus on what is free and try to sample the best from that. But behavioural economics also shows us ways to get past the free-rider problem and get people to pay for news.
There is a view that "if we figure out what people value, they'll pay for it". (e.g. these comments from @jangles and @katie15price on the #askeconomist conversation) This is not enough, though. For more on why this doesn't work, and an exploration of the business model question much more broadly, please do download our report on the behavioural economics of media and publishing.
And for more on the editorial model, try this from Jay Rosen as a starter.