Above: Illustration by Michel Royon.
Instagram is the richest and most vital visual-image database ever assembled: at least a trillion images that document every facet of human existence, endeavour, behaviour, and interests. However, unfortunately, the material on Instagram is currently largely inaccessible. This extraordinary database is currently wasted-and-rendered-unusable for historians, sociologists, psychologists, and visual researchers across many disciplines.
As with any profuse image database the key to usableness is some technology which enables the researcher to narrow-down the results served so that the investigator sees only what is relevant to his-her pursuit. Tagging images with search terms is typical in any such database of photo-images. But, sadly, in the case of Instagram, this procedure is unfortunately carried on ad hoc by individual users (the original uploader) using the "hashtag" feature. The tags added to many photos are not very specific (#bestdad; #instacool; #cool; #soblessed, etc.), and so searchability is very limited.
For example, if I search Instagram for images of humans with a mohawk hairstyle, the results served to me will be dependent on end-users adding that particular tag to any given photo. In the current inefficient set-up some of the most fascinating-and-relevant photos will probably not have been tagged #mohawk. (And will therefore not show-up in search results.)
One way of dealing with this lost opportunity would be for Instagram to offer free training to users on how to add specific and relevant search terms (hashtags) to photos--with this activity encouraged as an important public service. Another possibility is the use of AI cataloging bots or AI tools. We hear so much about AI, but when will any company start using it to add value or extra functionality for the end-user?
(22 May 2018)