The dashboard analyses from Social Monitor and Tweet Archivist present the statistics in a nice visual manner. But I am not sure that they tell me anything I didn’t know, however, if I was presenting this information to others then they would be very useful.

The busiest time was Friday 13 March; certainly true for myself as I was able to participate on this day.  The topics under discussion, and the sites linked to, kept very closely to the course themes of algorithms, learning, education and data; this is not surprising as the questions we were primed with revolved around these. The hashtags look slightly different with #codeacts and #learntocode featuring very heavily;  I wonder if this was because most of the conversations did not use hashtags so when one was introduced it quickly made an impact on the statistics.

There were a similar number of original tweets and replies which imply that conversations were brief. However, it is also likely that because we were using Twitter synchronously people were not using the reply button in the conversations; possibly because they take up valuable characters. From my point of view, as a participant, it did feel that there were lengthy conversations with several participants taking place.

@SianBayne features as the most influential tweeter with the most mentions and the most klout.