Twitter Analytics and Humanities

For the past few terms I’ve been exploring Twitter in my classes, in various ways, with tons of openness to allow students to influence and have input on the course use of Twitter. Now that I have several semester practice I’ve been exploring Twitter Analytics as a way to understand what students have been doing. Here’s what i’m finding:

  1. Twitter Analytics were designed for business reach so most free programs are only somewhat helpful to classroom use. By somewhat I really mean barely. Analytics and data track numbers and quantify data. While these analytics can amass our obsession with memes and gifs in cool ways – the number of posts don’t accurately represent the quality of the posting and connections developed (hello future digital humanities project)
  2. Student exploration of Twitter Analytics is fun because they notice that the analytics strive to capitalize on their individual use. Humanities students are amazing at analyzing and understanding the representation by numbers and of numbers. They offer in depth discussion on how those numbers don’t accurately represent the connections they’ve built through the assignment!

I’m impressed with the engagement in the course demonstrated by my students. But I don’t feel the Twitter Analytics I’m finding accurately represents their learning, nor would content analysis of the tweets (especially with the high volume of memes).

As I move forward with this assignment, and ask other types of classes to engage with Twitter conversations I’m wondering:

  1. What am I noticing in their posts that shows engagement?
  2. How does the assignment initially reward engagement?
  3. How do students branch beyond the assignment in their engagement?
  4. How do students in various classes interpret the assignment and use Twitter? and how do I ‘measure’ that?

Twitter is an amazing tool for fostering engagement and conversation, helping students build strong support systems within the course, and ways of engaging with course material both digitally and in the class. The struggle is in the measuring of this, in being a part of the developed Twitter course community and not being able to make it strange to understand and qualify the writing work occurring. The next step will be to consider how to make the engagement strange to offer suggestions for similar implementations, to consider how the assignment is designed and how it can continue to be improved.

The big finding is how adept students in digital rhetoric courses are at understanding how Twitter Analytics and Big Data operate in contemporary culture. Their insightful discussions demonstrated the need for digital rhetoric scholars to begin considering ways of understanding Twitter interactions beyond data analytics. I can see a need for future work addressing questions about Twitter use, Twitter application, and how users understand Twitter trend development.


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