Attention, not quality

A Wordle word cloud from the article below

Things come and go so quickly online, and it is still hard to keep up. Reading something interesting on a blog, article or tweet that soon after becomes so vital that I have to retrace my steps to unearth it to ensure it isn't lost to me forever is a familiar one. There are still times when it feels like sand slipping through the fingers. We rate as we read, but as the most recent sessions in the #citylis DITA module have shown, there are ways to find out which research is getting the most attention.

Altmetrics picks up on the impact of scholarly communication through social media and blogs long before citation counts take effect, perhaps years later. Altmetrics is, perhaps, like the thermometer in the mouth of research, picking up on just how hot (or not) open-source published material is. But altmetrics is an indication of attention, not quality, as I seem to have written in my notes more than once. Attention, not quality.

With the rise of digital come opportunities to analyse and explore, to corral datasets into useful ways of finding insights and unearthing what has been overlooked or unrecognised. Coding with Python is an area for me yet to explore fully. Word clouds, while simple and engaging to experiment with, do not analyse text in a way that is particularly revealing. (The one above has been created from this blog post, and reflects the way that I keep repeating the words attention, not quality.) Digital humanities, although typically unwilling to be precisely defined, is an interesting arena where digital media and scholarly research meet.

And should we be afraid of AI? Am I a Singularatarian or AItheist? It is hard to come to a categorical decision with Floridi's argument without oversimplifying the argument. Much of AI seems to me to be promising and romanticised, or as prosaic as Amazon's recommendations and fraud detection. Useful and largely unrecognised by most of perhaps, but yet to really find its greatest moments.