Building a Media-Activity Analysis Tool for Twitter

One Step Closer
As of mid-November 2019, my Twitter Developer application was officially approved by Twitter.

This was a thrilling update for two tightly-related reasons:

  • the approval provides me with developer access to Twitter’s API;
  • which, in turn, gets me one step closer towards building a media-activity analysis tool for Twitter (as a third-party developer).
What is media-activity analysis?

As my term ‘media-activity analysis tool’ reveals, it’s an analysis of media-activity levels specific to media-related content, either online or, as in my case, across a particular platform, namely Twitter.

What constitutes media for this appdev build project, however, is largely defined by Twitter, because my media-centric search tool will be querying media-specific data by way of Twitter’s API, which would not be possible to achieve without first getting approved by Twitter to do so.

Why media activity analysis and why Twitter?

The simplest of reasons behind wanting to build a media-activity analysis tool is this:

I’m a media psychologist and, as such, I care about media as a whole but in particular, I’m most concerned with our media construction and publishing, our media interactions and  consumptions, and our use of visual storytelling as a narrative mechanism.

And as for why Twitter, its platform just made sense (at least, as a starting point) to me while I was  ideating possibilities of a media-activity analysis tool:

  • its platform is conducive to global conversations in real time
  • global conversations, in turn, facilitate the propagation of media as an integral part of network communications
  • the Twitter API is both media-friendly, accessible, and configurable enough to meet my vision for media-search criteria
It’s also about visual storytelling.

As a media psychologist, narrative designer, and creative strategist, visual storytelling is an arena of high interest to me and those I work with; visual storytelling is how most of us (brands in particular) “talk” these days, where everything is communicated through videos, memes, animated gifs, image galleries, and more.

As a behavioral scientist, I also seek to explore the collective breadth of visual storytelling today.

I’m specifically looking for correlations in visual storytelling levels between brands as well as how visual storytelling activities may fluctuate or expand over periods of time.

While I realize that Twitter is only one platform and not representative of all online populations, it offers an exciting starting point from which to commence my media-centric explorations; a starting point made possible by Twitter’s approval of my Twitter Developer application (which was no small feat as one has to prove to Twitter how one intends on using their API to their satisfaction).

At any rate, I’m quite eager to forge ahead with development and will write more about this media psychology-inspired project in the coming months to share progress, lessons learned, and more.


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