Tweetorial analysis – Where is Angela?
For my analysis of the Tweetorial, I have looked at two categories and (“Top Users” and “User Mentions”) and added another two (“Mentions per Tweet” and “Average rank”). You can look at the Excel spreadsheet I created here: mscedcanal
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Here is a screenshot of the spreadsheet.
Selected questions arising from the provided data analysis:
Angela Tsui did not take part. Did anyone even realize? Is it because she is in Hong Kong? Is she?
Jeremy and James got the most mentions. Does this reflect power structures in the course?
Philip sent the most Tweets, but his “mentions per Tweet ratio” is somewhat low. Does this say anything at all?
Philip’s timezone is hours behind. He sent the most tweets. Angela’s timezone is hours ahead. She has no Tweets. What does this mean?
Eli has no top five rank in “number of Tweets”, “mentions” or “mentions per Tweet ratio”, but ranks at position 5 overall. tweetarchivist would not have given her due respect. What does this say about tweetarchivist or Eli’s performance?
Leaving out course tutors Jeremy and James, the top overall users are Nigel, Renée, Eli, Daniel and Colin.
The following users ranked in the top 5 at least once: Philip, Colin, Nigel, Helen, Jeremy, Eli, Renée, Daniel, James, Stuart and Ben.
Who are Ben Williamson, Monica Bulger and Jo Glover?
Monica Bulger, Ross Garner, Jo Glover and @Dirkster71 got mentions without tweeting. Does this make them super important/ relevant? Did they simply forget to include the #mscedc hashtag? Why do the not show up in the “mentions per Tweet” category?
Dirk Schwindenhammer has two Twitter accounts (and others possibly, too). Does this influence the results?
Do language barriers influence Twitter behaviour?
Is any of the presented data and data analysis relevant at all? Does it say anything about quality?
“Number of Tweets” and “mentions” are data provided by tweetarchivist.com. “Mentions per Tweet ratio” and “average rank” are data provided by Dirk Schwindenhammer, based on the data provided by tweetarchivist.com. Are any of the categories of any use?
Did instructions provided by the tutors prior to the Tweetorial influence behaviour and how?
2 thoughts on “Tweetorial analysis – Where is Angela?”
Great reflection on what is missing in the data, Dirk. Thanks for sharing.
Regarding my mentions per tweet ranking, here’s some data from outside the ‘window’: I’m pretty sure the cause was simply my ‘early’ response to tweets.. which was influenced by ‘cultural-based time zone factors’, since in my region Friday is a weekend day (meaning I could respond quickly to James’ tweets on Friday morning without work interrupting .. ), and I’m +3 GMT so wasn’t sleeping till the later tweets.
‘Is any of the presented data and data analysis relevant at all? Does it say anything about quality?’
Wondering, do you have any ideas about the kind of analysis (and method) that would (or rather ‘might’) produce a relevant, meaningful interpretation? For example, if you were interviewed about the experience, and asked about what you found most useful/meaningful or which of the Tweet (either questions or responses) prompted the most thought on your part, or about what you felt or thought at the time, would we get closer to ‘relevant’? & if the interviews were repeated with all participants? It would be time consuming, yes, but.. would it reveal something worth uncovering?
What if (for a touch of the creepy) your web-camera had filmed you while tweeting, and captured signs of your mood, algorithmically interpreted? Or measurements of delay between reading a tweet and responding to it?
What in your mind is missing from the data that is required to make it meaningful?
Thanks again,
Renée