Anatomy of a Museum Twitter Bot
In a group of eight Twitter bots distributing content from eight museum digital collections, none are affiliated with the collections they harvest from.
From this group of Twitter bots distributing content sourced from museum digital collections, we can take a closer look at who they are and how they’re changing the discoverability of digital collection content.
You can tell a lot about a Twitter account from an account bio — it’s origins, it’s function. The same is true for this group of museum Twitter bots. In this group of 8 museum Twitter bots, all accounts use this space as an opportunity to tell us something about themselves.
Looking at how this group of bots circulate collection content, we can use this field to garner more information about their methods — Brooklyn Museum Bot’s writing, “I am a bot that tweets one random object from the Brooklyn Museum collection, four times a day”. In reviewing what content is circulated, 6/8 bots circulate exclusively random collection content. This field can also tell us more about the frequency at which content is posted — 7/8 bots posting 4 times per day.
This section of the Twitter profile can also tell us more about the origins of a bot. In this space, of the 8 accounts in this group, all link to the Twitter account maintaining the bot. Of the persons responsible for this group of museum bots, one is most prolific — John Emerson — a Brooklyn resident operating under the handle backspace — who manages 6 of 8 bots in the group — explaining many of their shared practices.
As a point of distribution for digital collection content maintained by a host institution, all accounts in this group use this space to attribute the collection’s source institution and state their status as unaffiliated bots. In this group of eight bots, all accounts include a link to the item record when sharing collection content in tweet format — directing their audiences to learn more about the content as presented by the host institution.
From an audience perspective, museum Twitter bots offer a way to passively interface with collection content for inclusion in a larger stream of media — providing an alternative user experience while directing users to the content’s original source.
In museum digital collections, the discovery process connects user and content — guided from browse, search, and collection highlight functions. By stripping away infrastructural supports in exchange for randomized automation, Twitter bots remix the discovery of museum digital collections content.