Social Media Infrastructures and Algorithms and User Identifies Online

Social Media Infrastructures and Algorithms and User Identifies Online

Social Media Infrastructures and Algorithms and User Identifies Online

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Social Media Infrastructures and Algorithms and User Identifies Online

The utilization of social media supports a significant amount of people’s identities and daily activities. Social media platforms rest on digital infrastructures and algorithms. This makes it crucial to understand the influence of algorithmic changes and how to deal with them to serve both work-related and personal identities, goals, and purposes. The zeal to understand the impact of algorithms and within social media platforms is no longer left for mathematicians and computer professionals. Interests in these social media algorithms and their influence starting from how the infrastructure and algorithms are designed, have advanced beyond the common computational understanding of efficiency and optimization towards organization, societal and human understanding of its effects and applications. This paper sheds light on the socio-technical interplays that occur when people attempt to understand the way social media infrastructure and algorithms function and how these algorithms affect a person’s professional and personal identity.

Algorithms are step-by-step instructions that are used for problem-solving. They are constantly used when completing numerous tasks in our daily lives, for example, purchasing items online, predicting the most effective traveling route to the office, or even making forecasts on how a pandemic outbreak could be contained. Therefore, they are straightforward computational procedures consisting of specifications and direct descriptions of the kinds of steps to efficiently solve a problem or a task (Milan, 2015). However, how they operate could appear ambiguous to social media users. How the social media infrastructure and platforms work and how they affect the user’s identity, professional identity, and society is discussed from the individual users’ perspective and the wider society.

Since social media platforms are also professionally used, professional personnel have an emerging trend to manipulate the dominant platform algorithms for their work purposes. Many computer programs are developed with algorithms geared at bringing the user to a specific pre-defined goal in as few steps as possible (Carah & Angus, 2018). Professional work that entails using social media infrastructure such as the ones provided by Instagram, Facebook, and Twitter are made of and often redefined by the owners of the platforms. They are also redefined by the different types of users’ data that consist of encoded users’ behaviors and other information, touching on how the user navigates and uses the platform. The large volume of data that continuously flows through these social media infrastructures makes the algorithms’ lifecycle relatively short (Woolley & Howard, 2016). Social identities are the images derived from the relationships formed online. Social identity groups include those that are, for example, formed through mental, social, and physical characteristics of people including gender, sexual orientation, age, race, ethnicity, religious beliefs, socioeconomic groups, social class, abilities, and so on. Social media uses these identities as part of its algorithms to include diversity and in data collection. This means that the algorithms should be dynamic and constantly changing. As they change, the social media users’ work of understanding how they operate and their online identities are also subject to change. The interactions of different users online and their willingness to share their data form the crucial resources for social media infrastructure owners to mine data and customize the social media algorithms. Therefore, these algorithms are critical agents of the socio-technical two-way arrangement of platform owners and platform users.

From the professionals’ perspective, how information is shared on social media infrastructure and the algorithms lurking behind how they operate is relatively unknown. Platforms like Facebook are not static. Such platforms could be understood as dynamic, growing infrastructures in which the algorithms are cultivated and improved over time. Because of uncertainty over how social media algorithms change and operate, professionals’ tasks and online identities that use these platforms are due to change (Napoli, 2015). Therefore, working with social media sites is described as a continually changing entanglement of professional identity, tension, and technology where it is crucial to adapt to the key components.

Social media platforms have become immensely popular for professional use geared towards increasing the citizens’ participation efforts in local governments. This is because they are platforms that citizens are already familiar with from their regular private use. The social media infrastructure stimulates sociality and creativity in a way that most conventional government platforms do not. Instagram, Twitter, and Facebook are a group of social media infrastructures that are distinctive in the sense that they have allowed people to self-design their identities and increase their visibilities on social networks (Napoli, 2015). With the algorithms at play, being social on social media is not only an act of making a person’s network visible to a group of people that you are already familiar with. However, it is a performance that has been constituted by the users’ regular engagement in connections and content-driven and inspired by social media algorithms and business logic (Woolley & Howard, 2016). Social media algorithms could help local governments to improve their image or identify in the eyes of the public through exploiting the algorithms’ ability to make a particular news item to trend or sponsoring content that paints their work in a positive light.

As working with social media is becoming more common, an accurate understanding of the platform algorithms’ interwovenness and work has increasingly become salient. The social media infrastructures are enablers of a set of double logics. Their duality is also a double-edged sword of empowerment of the platforms and their users. This means that, on the one hand, these platforms can steer connections and content to their users based on their commercial logic. On the other hand, these social media platforms are still dependent on users to share their identities and interaction data with the various platforms (Woolley & Howard, 2016). In this kind of interplay between the platform users’ and owners’ commercial interests, the algorithms become intriguing. They serve as a boundary item between the platform users’ identity and the owners, with both sides being similarly interested in harnessing the algorithms to suit their various purposes.

Rating and relevance are crucial aspects of the algorithms woven into the infrastructure of social media platforms. Relevance is based on what the user in past interactions online has shown interest in. This is primarily the kind of content that has been shared, commented on, liked, or the kind of content generated by other users who interact with him. Depending on how the user adapts to the algorithms, other users interact differently with various social media posts (Milan, 2015). It should also be noted that depending on the engagement levels on posts and the negative and positive reactions originating from the users, professionals and their unique attributes or identities who work with these platforms will be rated by the users and the algorithms (Woolley & Howard, 2016). Such a rating is crucial data that gets fed into the algorithm of the specific social media platform. The algorithm would therefore shape future connections and content that will be visible to the users. This means that it is the algorithm that will structure the content available to the user based on the data and information collected concerning the user’s attributes, likes, and general identity. The platform owners aim to develop even more relevant services for the users and make even more accurate predictions touching on user demands and preferences.

Social media change elements and algorithms work as a concept employing socio-technical interplay. Initially, the socio-technical approach was primarily a response to overcome the opposition between social and technological determinism. Still, it was criticized for being nothing more than an instrumental normative tradition. The practices’ practical impact involved in socio-technical research has also been probed over the years. The role of technology and how interactions between people, technology, and organizations occur are yet to be fully understood. Several decades later, it is still common to see literature has yet to delve deeper into how dynamic algorithms and the ambiguity of their operations affect the way people are going about their personal and professional duties. There was a time when the hardware view prevailed as a multiple-context specific technology definition standard in organizations that mostly used machinery (Woolley & Howard, 2016). However, the modern changes as elaborated in the discussion area on a distinctively different level. There is still the need to delve into the socio-technical interplay and what takes place during activities that are affected by the ever-changing elements of infrastructure, algorithms, and user identity within the platforms used for work-related tasks.

The paper presents the case for a call for comprehensive discussions between social media infrastructure, algorithms, and their interplay with user data and identity. This has been achieved through an in-depth evaluation of how algorithms affect professional and personal interactions on social media platforms. The paper’s main contribution lies in conceptualizing algorithmic work, what it entails, and how it works with social media layout and media. It can be stated that algorithmic work is a socio-technical relational arrangement between social media users and the algorithms. The structures and performance of algorithmic work constitute adjusting the actual social media and user operations and interactions as the algorithms change.


Carah, N., & Angus, D. (2018). Algorithmic brand culture: participatory labor, machine

learning, and branding on social media. Media, Culture & Society, 40(2), 178194.

Milan, S. (2015). When algorithms shape collective action: Social media and the dynamics of

cloud protesting. Social Media+ Society, 1(2), 2056305115622481

Napoli, P. M. (2015). Social media and the public interest: Governance of news platforms in the

realm of individual and algorithmic gatekeepers. Telecommunications Policy, 39(9), 751-760.

Woolley, S. C., & Howard, P. N. (2016). Automation, algorithms, and politics| political

communication, computational propaganda, and autonomous agents

Introduction. International Journal of Communication, 10, 9