A belated post about the recent (OK, more than a week-and-a-half ago) computational journalism seminar at HKU’s Journalism and Media Studies Centre. It was a short session – just two hours – but offered up a number of interesting ideas and insights.
There were a couple of presentations – including the SCMP’s Irene Jay Liu showing off WhoRunsHK, as well as King-Wa Fu of JMSC demonstrating a project to track and sort (and translate) major microblog feeds in China and Hong Kong. And Jonathan Stray, via Skype, showed some things that are being done around the world, including at the AP.
But the non-demonstration stuff was just as interesting – in particular, the ways Nick Diakopoulos of Rutgers and Jonathan tried to categorize the emerging field of computational journalism. This isn’t new, of course – Jonathan came up with a taxonomy a little while back – and it’s certainly not definitive. But given a field that spans the distance from corwdsourcing to twitter to semantic engines to statistics and datamining, it’s a good idea to try to understand what fits in where.
One way (from Nick) of breaking up the disciplines of the field – and of course there’s tons of overlap – was in terms of using technology for:
- Gathering information (everything from classic computer-assisted reporting to crowdsourcing);
- Sensemaking and organization (datamining, CAR, semantic engines);
- Presentation and communication (visualization, interactive databases);
- Dissemination and tracking/enabling public response (twitter, social media, but also targeted distribution of information to people in a position to use it or be affected by it).
I’m sure I’m not doing this justice, but even with my poor note-taking this looks like a good framework. Jonathan had added a range of other segments, including tracking the spread of information; and both had raised the critical issue of following response to information – is it enough to just publish, or should we work on making sure stories have impact?
And within all those sectors, there were another alleys to explore, from news games to automatic content production to exploiting the ubiquity of devices and data (Nick raised the possibility of reaching out specifically to people near an event – identified on GPS – for their help in reporting.) And in the areas I’m interested in, what are the impacts on the newsroom process, the new products that can be created, and how we can make money from all of this.
All heady and interesting stuff, and a sign that computational journalism is making inroads on this side of the world as well.