“The Spy Who Loved Me”: A Qualitative Exploratory Analysis of the Relationship Between Youth and Algorithms

Abstract

This paper presents the results of a study which aims at understanding how social media platforms influence the formation of opinions of young adults (18–25) through content personalization. To do this, we problematize the so-called “filter bubble” phenomenon. We first go back to the literature and propose to depart from trying to assess the existence of and quantify the presence of filter bubbles on social media. We propose to focus on news use and access to content diversity related to political opinion formation and the impact of algorithms on the presence of said diversity. We then propose a theoretical framework—Activity Theory (AT)—for the understanding modeling the diversity of practices as well as the discourses regarding these practices of youth on social media regarding access to the diversity of content and news. In particular, the division of phenomena in three levels (operations, actions, and activities) is used to build up a canvas for a model that will be tested enriched with the new data. The so-called “pyramidal model” is also discussed and applied to our research topic. The third part of this paper summarizes the methods used to gather the data through a method we call “online in praxis interviews.” We then present the results, which show a relative knowledge of the mechanisms of content recommendations on social media as well as the tactics young people use to increase or mitigate them.

Testing influences of openness, conscientiousness, nationalism, media diversity, social class, and informational echo chambers on support for official responses to COVID-19 in Wuhan in November, 2020

“…Since the Internet platforms have become the main channels for people to access information, we propose to focus on using Internet platform algorithms to reduce echo chamber acts ( Wiard et al, 2022 ). For Internet platforms like Tik Tok and Toutiao.com , an echo chamber user identification mechanism should be built based on users’ personality, ideology, media contact behaviors and social class.…”