Are you stuck in a YouTube bubble? It’s time to expand your information sources!

Analysis of Youtubers’ comportment in News & Politics category

This image was generated with DALL.E from CHatGPT

Nowadays, most of the information we consume is digital-literature, pictures, videos, you name it. There is an endless stream of content out there, but there’s a catch: fake news! Not everything you see can be trusted. So how do you avoid getting caught in the trap ? Simple: stay informed, and by that we mean mixing it up, diversify your sources.

For many, YouTube comes to mind as a go-to platform for diving deeper into any topic. Whether it’s for entertainment, learning or exploring the latest debates, This social media giant offers a massive variety of users and videos . Some people love exploring a broad range of videos or channels, while others stick to similar content within the same channel. We are going to group users into different clusters, in this case based on their commenting activities in a specific channel. Such clusters reflect communities invested into the same channel, but don’t yet imply that they are not diversifying their sources to retrieve information on a particular topic.

What we want to find out is whether these clusters can be considered to be bubbles, meaning that users are confined within the cluster, limiting exposure to other information sources. Furthermore, interactions are mostly between individuals who share the same interests, whether it’s the same video subjects or channels followed.

An area where we expect to see such bubbles is News and Politics (N&P). Why? Because N&P is inherently polarizing, thus tending to the establishment of strong opinions and engagement from diverse groups of people. This leads to some intriguing questions: Are clusters in our dataset indicative of bubbles with limited perspective diversity ? Do commenters of major news channels form bubbles, or do they behave similarly to random YouTube users ? How isolated are the bubbles within the N&P community ? For what purpose do the identified bubbles use N&P content (e.g politics, daily news, etc.) ? Are the bubbles isolated due to the media they refer to, or the common topics of interest ?

To dig into these questions, we will first explore YouTube’s dynamics, focusing on the journey from content creation to how users engage with it. Secondly, meaningful users-clusters will be identified to go beyond the individual activity of each user to have a look at the group effect. From those identified clusters, shared viewing patterns will be uncovered by the creation of bubbles. Finally , in those bubbles , connections between shared videos will be unveiled.

To address these questions, we will first explore Youtube’s dynamics, focusing on the journey from content creation to how users engage with it. Secondly, meaningful users-clusters will be identified to go beyond the individual activity of each user to have a look at the group effect. From those identified clusters, shared viewing patterns will be uncovered by the creation of bubbles. Finally , in those bubbles , connections between shared videos will be unveiled.