Do Social Media Algorithms Lead to Harmful Social Polarization?

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Table of Contents

Introduction
Body
Conclusion
References

Introduction

There are numerous social issues that are underpinned by the growing role of digital platforms. The abundance of online content authors nowadays makes people with different views dependent primarily on the sources of information that comfort them. Therefore, people have become more inclined to reject any portions of information that may question their holistic approaches to certain issues.

At the same time, online information tends to be one-sided, which gradually diminishes the chances of finding compromise. It can significantly undermine the functioning of various social institutions that have proven to be instrumental for the development of a sophisticated democracy.

Moreover, businessmen who control social media have developed sophisticated censorship systems that reflect their values and political views. Given millions of voters’ remarkable variety in political views, the phenomenon was destined to cause tensions and undermine the perceived sustainability of certain online platforms.

Therefore, current news feed algorithms and severe censorship used extensively to form public opinion accelerate political polarization.

Body

Paragraph 1

Firstly, the Internet, in general, has become highly structured and polarized and is no longer underpinned by the peaceful coexistence of narrow-topic forums exploring practical issues or encouraging discussion.

Moreover, Bail et al. (2018) state that even traditional media have become dependent on Facebook and Twitter as news sources and public opinions.

However, some people argue that the influence of social media cannot be compared to the impact of TV channels that receive remarkable funding.

Although this may be true, the public is more interested in interactive and engaging online communication with real people.

Thus, despite all the sponsors and funds that are allocated by political parties to traditional information distribution channels, social media have started to dominate the formation of public opinion. This fact allows people to control the feed algorithms to manipulate the political views of millions.

Paragraph 2

Secondly, the Internet has changed significantly since the 1990s and 2000s, with search engines and algorithms determining the trends and providing the news.

For example, Levy (2021) claims that social media algorithms avoid recommending counter-attitudinal news and any other type of content.

On the other hand, some may argue that the potential introduction of various perspectives in news coverage is a less significant political factor than income and background.

Although this may be true, the US presidential elections are primarily dependent on a few communities that have a large number of people ready to change party allegiance.

Thus, several political phenomena that determine US politics can be manipulated by people deciding to censor particular types of news.

Paragraph 3

Thirdly, there is an apparent lack of variety in the social media market. Facebook and Twitter dominate data collection, analysis, and provision in most regions of the world.

For example, Yarchi et al. (2021) underline that particular social media contribute to the polarization of society by encouraging prevailing contexts.

In contrast, some may argue that social media provide a platform primarily, while people’s preferences are formed by their online interests and news.

Although this may be true, several IT specialists still have remarkable influence over the selection of topics for discussion and censorship of perspectives they personally do not approve of.

Thus, a single group of IT specialists who tend to be on the far left of the political spectrum can ban a person, a point of view, or even a topic for discussion in any region of the world.

Conclusion

Public discussion has always been considered instrumental for a well-functioning democracy. At the same time, a wide range of policymakers have discovered the remarkable power of digital tools that ensures rapid transformation of public opinion. The control over an influential TV channel can currently be less significant than popularity on social media. Moreover, the active discussion that follows every political statement on Facebook or Twitter can be channelled in a way that can multiply the original effect.

Thus, a new regulatory system is needed that hinders the chances of severe political content censorship underpinning current algorithms. Whenever a censorship occurs, only people with the “right” stance are given a chance to provide rationale, which significantly decreases the number of available solutions for certain nation-wide problems. Moreover, such control over social media creates an illusion that the majority of the population agrees with certain issues supported by censors. This leads to rapid marginalization of large parts of the population who may partially disagree with certain minor issues but lack the ability to provide reasonable arguments for the development of a sustainable, universally approved solution. Therefore, numerous current political tensions that undermine the functioning of various countries due to lack of dialogue can be avoided by ensuring that social media platforms are neutral.

The only alternative is the development and establishment of new social media that will be chosen by people who feel oppressed on Twitter and Facebook, which will further exacerbate political polarization.

References

Bail, C. A., Argyle, L. P., Brown, T. W., Bumpus, J. P., Chen, H., Hunzaker, M. F., Lee, J., Mann, M., Merhout, F., & Volfovsky, A. (2018). Exposure to opposing views on social media can increase political polarization.Proceedings of the National Academy of Sciences, 115(37), 9216–9221. Web.

Levy, R. E. (2021). Social media, news consumption, and polarization: Evidence from a field experiment.American Economic Review, 111(3), 831–870. Web.

Yarchi, M., Baden, C., & Kligler-Vilenchik, N. (2021). Political polarization on the digital sphere: A cross-platform, over-time analysis of interactional, positional, and affective polarization on social media. Political Communication, 38(1-2), 98–139. Web.

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