Automated Bots – the Mission of Creating Filter Bubbles

Are you aware of that even the smallest actions you do and the likes you give online, can put you into a filter bubble? In our investigation of filter bubbles we use automated bots as our own test subjects. If you don’t know what a filter bubble is, read our first blog post to find out more ( This Wednesday, 14th of March, we are speaking at the Women in Data Science conference in Stockholm about our work.

For the mission of creating filter bubbles we are using a large social media platform as our tool. A user of this platform has access to a flow of information. This flow is individualized for each user based on its actions and behavior on the platform. We are creating 14 unique accounts on this site, extremely similar to one another, with the exception of username, email and IP address. The purpose is to have the individualized flows exactly alike in the beginning. For each of the 14 accounts, we are creating a bot (total of 14 bots). A bot is an automated software, designed to click and use the website just like a human would. In this case, each bot is hitting a like-button for a certain type of information, a certain amount of times per day. This is simulating a real user’s actions on the site. The information that is liked by the bot, is uploaded to a storage on the cloud, that we are using to investigate the behavior, potentially leading up to a filter bubble.

In order to get the data from the individualized flow, we use a crawler. The crawler go through the individualized flow and save the important parts to a file which is then uploaded to the cloud. The data is later used to evaluate the content of the flow to establish whether the user is put in a filter bubble or not. To get a deeper understanding of filter bubbles and whether they can be harmful, we conduct a literature study as well.

Our names are Anna Normark and Rebecca Oskarsson. We are two master students in the IT engineering programme, currently working on our master thesis. Our thesis consists of investigating filter bubbles and their effects, and have the title “Individualizing Without Excluding: Ethical And Technical Challenges”. We are invited to write some blog posts here by our reviewer Åsa Cajander and this is our second part.

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