Tweetorial Analysis

Tweetorial Analysis

I see you, I hear you, I acknowledge you.

Source: https://giphy.com/gifs/twitter-10shHccb7Xfn2g/links

I’ve struggled to come up with a unique analysis of our Tweetorial in #mscedc. I am unsure of how to take the data presented in the archive and transform it into some sort of academic critique. Besides providing us with quantitative data (top users, top words, top URLs, source of tweets, language, volume over time, user mentions, hashtags, images and influencer index), what meaning do these numbers give us and what is the significance? Did we, as a class, create any broader connections to each other or to relevant academic work from our participation in the Tweetorial? If we did create connections and relationships through our intensive two days of tweeting, then what can we glean from these connections and relationships and what is the meaning and value of them (Eynon 2013)?

In our Hangouts tutorial on March 21, I mentioned my love for ‘liking’ tweets and how this miniscule effort of seemingly passive participation, albeit small and arguably insignificant, is important to me because it is my way of letting my colleagues know that I see them, I hear them and I acknowledge their efforts and contributions to the Tweetorial event. It is so easy to simply click the heart and ‘like’ a tweet, but I really feel that by doing so, others will (perhaps) feel validated and – dare I say – more confident to keep contributing. I also believe that ‘liking’ provides a sense of belonging for both me and for those whose tweets I like.

 

Through our ‘data trails’, we did seem to connect through strings of tweets – of 140 character digital conversations that created relationships between classmates, professors and outsiders, and that encouraged and produced learning (Siemens 2013). Our conversations directed us to articles, images and to our own EDC lifestream blogs. I took some time to review my classmates’ Tweetorial analysis posts, and have collected their posts here:

Matthew, Renée, Eli, Colin, Chenée, Clare, Stuart, Daniel 1, Daniel 2, Philip, Helen M 1, Helen M 2, Helen W, Myles, Linzi, Dirk 1, Dirk 2, Cathy, Angela, Nigel

Via Daniels’s blog post, I found the Tags Explorer site, which I plan to use in a video artefact I will create for the Tweetorial event.


References
Eynon, R. (2013) The rise of Big Data: what does it mean for education, technology, and media research? Learning, Media and Technology. 237-240.

Siemens, G. (2013) Learning Analytics: the emergence of a discipline. American Behavioral Scientist, 57(10): 1380-1400

4 thoughts on “Tweetorial Analysis

Leave a Reply

Your email address will not be published. Required fields are marked *