Tweetorial Twanlytics

How has the Twitter archive represented our Tweetorial?

It has sequentially archived all of our tweets. It has then produced a number of visualisations such as this.  It also gives qualitative stats and places them prominently as a banner on every page:


605 Tweets
3/5/2017 – 3/21/2017 Date Range
image description Active
What do these visualisations, summaries and snapshots say about what happened during our Tweetorial, and do they accurately represent the ways you perceived the Tweetorial to unfold, as well as your own contributions?

They are very good at presenting qualitative data but become more problematic once we try and assign meaning. For example, I have no doubt that the archive has accurately logged who tweeted the most, but I would dispute whether that makes them the “top” participant. On reflection I’m not sure I even would want to ask which student was “top”, either quantitatively or qualitatively,  as it goes against the kind of tutorial atmosphere I value e.g. supportive, free thinking, rigorous but low-stakes.  I imagine that these data are analysed mainly because they are very easy to capture, whilst the intangible qualities I am looking for are less so. This relates Knox’s point that we should ask what do these metrics say about what we value in our culture, rather than only debating whether they are accurate.


My impression of the tutorial was that it was pretty manic. The truncated format of tweets meant I often had problems decoding acronyms or unduly shortening the point I was trying to make. On top of that I was also very busy at work over those two days, making it hard to dip in and out of the conversation. These personal impressions are not captured in the visualisations as it falls out of the scope of the archives database. Here is a link to a suitable visualization which captures this impression.

What might be the educational value or limitations of these kinds of visualisations and summaries, and how do they relate to the ‘learning’ that might have taken place during the ‘Tweetorial’?


As mentioned above, the limitation of these visualisations is that that they cannot portray meaning or value. It relies on us to be digitally literate enough to be able to decode what the data shows, understand how it was gathered (which Twitter is apparently keeping secret anyway) and whether we can use Twitter competently to allow our data to be captured accurately (as mentioned in my previous synthesis).

On the other hand, perhaps it is the lack of set meaning that allows the twitter analytics to be used by both businesses and ourselves. It is not the archive visualisations that produce educational value but the framing of the visualisations provided by the course readings, student and teacher discussions in the lead up to the tweetorial and then this mandatory critical analysis afterwards.