writing with a little help from your friends

I posted a draft of the paper I’m working on on Google Docs on Friday and asked for feedback and help – and already more than thirty people have looked at it and five people have left comments – and of course some people have messaged me to let me know that they’d like to but haven’t had time to read it yet. Reading and giving feedback on a 5000 word draft can be a fairly time-consuming process. But I must say, the feedback I’ve received is really useful, and even just the knowledge that people have looked at it and not had any comments is valuable. Part of the reason I want drafts out there before it’s published is simply quality control. The article is going to be published in the European Journal of Communication, and it will be vetted by experts in communications studies and copy-edited by experts in citation technique and so forth – but the editors aren’t experts in social media. And there are only a few of them. So getting feedback from more people is bound to help improve the article.

For instance, the core of my article is probably my sorting out of different ways in which social media organise our data into stories or patterns. Here they are (and I would love feedback on this!)

  1. Patterns that show TIME
  2. Patterns that show RELATIONSHIPS (and popularity?)
  3. Patterns that show CONTEXT (is this a subset of relationships? (or vice versa)
    • Friendfeed.com ñ gathers your data from several sources, shows your friendsí data from several sources
    • Dagbladet profile (I blogged about this)
    • Spock.com (same idea as Friendfeed)
    • Tumblr.com ñ creates a public site for your gathering your info from Twitter, blogs, Flickr, etc.
  4. Patterns that show GEOGRAPHY
    • brightkite.com (check in with GPS-enabled device)

    • dopplr.com (logs travels, creates visualisations for individual users, like this one it made for me)
    • Google maps ñ the customised/hand-crafted ones
    • Flickr map view ñ see photos on map
    • Nikeís running logs, using data from Nike/iPod running shoe thing-me-gig and allowing you to add geo-data (these also show time, development of runs over time)

I’ve received a few comments on this – I’m wondering how to present it, whether the division of categories makes sense, and what to do with it. Here’s how people responded:

I’ll be getting feedback on the draft from my colleagues in my research group too, but while they’re all very savvy about digital culture in general, none of them really specialise on social media – and so I’m very grateful to all extra feedback I can get. And of course, I’ve also asked Scott for feedback, and as always, his feedback is thorough and extremely useful. And maybe more customised than most – Scott knows my writing and can remind me of what I do well and gently suggest stripping away some of the blah blah (he wants more examples and less of the general and not-very-revealing references – and I think he’s right). Here’s one of his comments on the categories:

So do you think my categories of generated stories in user data make sense? Or do you have other good examples for me? Do share, please!

11. May 2009 by Jill
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