Do Social Media Algorithms Lead to Harmful Social and Political Polarization? Essay

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The research question is about the existence of highly efficient censorship and recommendation frameworks integrated into social media with the aim of forming public opinion.

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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.

The author claims that the abundance of authors currently ensures that people can always feel supported online, whatever their views are. Debates are no longer as popular as they used to be, which hinders the opportunity to evaluate different factors and arguments. The problem is that political information is considered extremely valuable, meaning that multiple political groups are willing to invest sufficient sums due to the high yield. Thus, a large proportion of online information is significantly altered to satisfy the sponsors. It does not directly involve fake news, as different perspectives and different sources of data used for making prognoses are substantial to form public opinion. I believe the major problem is that information is always one-sided and leaves no room for compromise. I am planning to use the study to prove that people often feel uncomfortable or even vulnerable when other parties provide logical arguments.

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

The author claims that the remarkable power of various social media has raised numerous concerns about the usefulness of the existing framework that determines the functioning of the news feed. People did not always feel obliged to label themselves online and act accordingly. The Internet during the 1990s and 2000s represented a unique place underpinned by unprecedented, which made people from different parts of the political spectrum to use value it and enhance it jointly. At the same time, numerous authors and communities could create content without the necessity to express political stances. Currently, sophisticated algorithms process large volumes of data that help to create a profile of a person that explores his/her views on certain issues. Once this is accomplished, social media start to recommend only the news that does not interfere with a person’s comfort zone and attitudes. I believe that before the rapid expansion of Facebook, the Internet used to represent a different kind of information transmission tool. The entire net was significantly less structured and polarized due to the peaceful coexistence of narrow-topic forums exploring a particular practical issue or encouraging interaction and discussion. I am planning to use the study to show the evolution of social media censorship.

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.

The author claims that social media owners have rapidly concentrated significant power and, purposefully or unconsciously, developed their own sophisticated censorship systems that reflect their values and political views. It made numerous people who felt oppressed by monopolists, such as Facebook and Twitter, and deprived of the ability to find compromise through discussion to rapidly move further right on the political spectrum. I believe that the vast majority of IT specialists tend to be on the far left due to a wide range of factors. I am planning to use this research to prove that these people’s high salaries make them less sensitive to taxes, gas prices, and numerous other issues that are significant for millions of Americans working in the real sector of the economy.

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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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IvyPanda. (2023, April 14). Do Social Media Algorithms Lead to Harmful Social and Political Polarization? https://ivypanda.com/essays/do-social-media-algorithms-lead-to-harmful-social-and-political-polarization/

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"Do Social Media Algorithms Lead to Harmful Social and Political Polarization?" IvyPanda, 14 Apr. 2023, ivypanda.com/essays/do-social-media-algorithms-lead-to-harmful-social-and-political-polarization/.

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IvyPanda. (2023) 'Do Social Media Algorithms Lead to Harmful Social and Political Polarization'. 14 April.

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IvyPanda. 2023. "Do Social Media Algorithms Lead to Harmful Social and Political Polarization?" April 14, 2023. https://ivypanda.com/essays/do-social-media-algorithms-lead-to-harmful-social-and-political-polarization/.

1. IvyPanda. "Do Social Media Algorithms Lead to Harmful Social and Political Polarization?" April 14, 2023. https://ivypanda.com/essays/do-social-media-algorithms-lead-to-harmful-social-and-political-polarization/.


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IvyPanda. "Do Social Media Algorithms Lead to Harmful Social and Political Polarization?" April 14, 2023. https://ivypanda.com/essays/do-social-media-algorithms-lead-to-harmful-social-and-political-polarization/.

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