Life(stream) comes at you fast: Week 7 summary

The most remarkable thing about my lifestream this week is the massive increase in content, particularly compared to the past couple of weeks. In a deliciously meta twist, the reasons for this are also, weirdly, the themes of my lifestream: reaction and community.

The mid-course feedback I received quite rightly suggested that I consider additional ways to feed content into the lifestream. I wrote about a specific (albeit rather miniature) dilemma I faced in response to this. The feedback also encouraged me to reflect further on how I’m using IFTTT. Adding posts from Pinterest, for example, like this one, require readjustment to make them fit, and the time it takes to fix them often feels double the time it would take to add the content directly. This helped me to shape a presentation given to grad students at work, focusing on employing IFTTT in a far more instrumental way than I am here. [Click the image below to see the slides].

Reaction and community intersect evidently in terms of the response of EDC community to the micro-ethnographies posted by me and my supremely talented classmates. This is demonstrated in a series of comments (here, here, here), many tweets, and follow-ups to read in our post-netnography haze (here, here, here). I also included my personal reaction to tweeting a piece of academic work. One particular thing I was intrigued by is the way our expressions of community on Twitter were often non-verbal; they were endorsements, RTs or favourites. I considered this further in a blog post about a viral meme.

It’s been a week of reconsidering what ‘community’ can mean, and the assortment of ways in which cohesion might be considered in relation to it. It isn’t necessarily active and present; the question might be ‘to lurk or not to lurk’, but this affects your community status, not membership.

One Reply to “Life(stream) comes at you fast: Week 7 summary”

  1. Looks like it has been a busy week for you Helen! The ‘automated’ aspects of your lifestream feeds is a useful reflection to bring into block 3, where we consider algorithms. The character of the lifestream – whether ‘massive’ or not – seems to be somewhat out of our control, and maybe that is an experience you’ll associate with ‘algorithmic play’.

    ‘One particular thing I was intrigued by is the way our expressions of community on Twitter were often non-verbal; they were endorsements, RTs or favourites.’

    Interesting point (and post) here. It strikes me that this quite often leads to different (quantitative) ways of researching ‘community’. I hear the criticism quite often that ‘likes’ and other endorsements are such a narrow and problematic form of measure, however your point here, and particularly in your other post, indicate their importance. Narrow perhaps, but capable of demonstrating the kind of solidarity that is rather important in current times?

    Nevertheless, the reduction of community interactions ‘likes’ makes them rather conducive to algorithmic processing, perhaps similar to some of the things we’ve seen with Facebook, and certainly with recommendations elsewhere. Useful connections between the blocks perhaps?

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