Bot logic refers to the situational effect of bots upon a socio-technical ecology and their potential to infiltrate and co-exist with server-side conditions. We propose the term bot logic in response to platform logic. Jonas Andersson Schwarz describes platform logic as:

the interplay between different mechanics inherent to digital platforms, found on different conceptual and topological levels: micro, meso, and macro. It is a way to simultaneously acknowledge the technical capacity of unyielding local control and its consequential concentrations of global dominance by a handful of corporate actors².

A platform according to him is a "digital infrastructure (software-based but sometimes also hardware-based) intended for users to apply either computer code in the conventional sense (i.e., to run applications or fetch data from it), or to apply a set of human uses (delimited, formalized, and patterned by the design of the platform in question)" (2017, 4).

Schwartz uses the term "platform logic" to describe the tensions that arise between the geopolitical level of the impact platforms have and infrastructural control that they acquire, more specifically that "a software system that provides a pivotal societal function in one jurisdiction can be thwarted by internal policy decisions made by a gargantuan platform corporation, based in an entirely different jurisdiction" (2017, 18).

To unpack the term bot logic further, we will explore four differences between bot logic and platform logic.

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• Where platform logic accumulates, bot logic disperses

On commercial digital infrastructures, the engagement of users creates economic value that is translated through data capture and organisation. Data is extracted from users and used to calculate relevance, make recommendations and target users for advertisements. While bots can and do support this economy, they can also undermine it. In the case of buying bot followers, for instance, this can be a means to generate noise in the collected dataset and blur the perception of the user as a set of behaviours that the platform makes available.

• Where platform logic centralises, bot logic fragments

Platforms such as Twitter or Facebook are built as centralized systems: the servers on which information is stored are owned by these companies. The servers are triggering the need for growing data center infrastructures throughout the world. Bots, on the other hand, do not require a lot of computational power in order to run. They can be simply executed from the computers of the bot makers themselves. In fact, bots really point to the materiality of the systems on which they run, as researcher Stuart Geiger points out when he talks about bespoke code:

[code that] runs on top of or alongside existing systems instead of being more directly integrated into and run on software-side codebases¹.

• Where platform logic creates distance between user and infrastructure, bot logic develops an intimate knowledge of the platform

If we consider means of communication as means of production³, there is a process of alienation that happens on commercial centralised platforms, where the user has no stake in the development of the material conditions of the platform on which they interact and communicate. From this perspective, the making of bots implies a closeness to the platform that is indicated through the understanding of both the sociological and technical systems that determine the usership of a platform. In order to write a bot, as mentioned before, you need to know what kind of actions are allowed and how the bot would be received by the community.

• Where platform logic reinforces habitual behaviour, bot logic encourages new habit formation

If we think about a commercial platform as a structure or surface on which actions can take place, these actions are often predefined by the affordances of the platform. However, bots are the automation of certain actions and behaviours. To be able to define these behaviours, a user needs to be provided with the means to alternate the socialities of a platform.

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These bot logic arguments were written with centralised platforms in mind. However, exciting developments are happening on federated platforms such as Mastodon, where users are part of defining features and possibilities of interaction.

To understand the differences between centralised and decentralised platforms, it is useful to compare two communication platforms that employ different network topologies and governance models: Twitter (centralised) and Mastodon (decentralised, federated)⁴. Both microblogging platforms have a significant amount of bot agents.

How does the way in which these bots relate to their infrastructures differ?

As opposed to Twitter, Mastodon is a free and open source self-hosted networking service. Anyone can become a node in the network by installing the software and thus federate with other servers. The nodes, or user bases, are referred to as "instances" which have community-determined norms. There, the norms of the platform and the way they are codified into the technical structure are more often revised and reformulated together with the people using the platform, such as a Code of Conduct.

Mastodon is part of a bigger network, which is also known as the Fediverse, which has grown into a social media space that is currently used by more then 5 million people. In contrast to social media platforms as Twitter, Instagram or Facebook, it consists of a whole range of different kind of social media: blogs, micro-blogging, photo sharing, video sharing, link sharing, etc., that can exchange posts and content with each other. Each instance does this, however, under their own terms. In contrast with the top-down organisation of centralized networks, the Fediverse and its federated network typology allow different groups to configure their network differently.

Each network is shaped by its stakeholders. Sometimes this is a single individual, sometimes a group of peers that share the same interest and other times an organisation. Often it is the system administrator(s) of a network who decides what the rules are: Who can publish? What kind of material can be published? What communication features are available?

With a different infrastructural system comes a different type of rule set. The federated network structure of the Fediverse also has consequences for bots. On platforms like Mastodon, bots need to both comply to the terms of services of the API and to community agreements, such as the aforementioned Codes of Conduct or Community Guidelines.

Footnotes