Social media is everywhere. Every time someone interacts with social media, whether it be liking, commenting, or even logging in for the day, that data is collected and forms a social media footprint. This information is used by the social media platform to show more relevant posts, or it is used by advertisers to show more relevant ads. For our project, titled “Social Media Footprint Awareness,” we investigated how user activity impacts one’s digital footprint.
To test and analyze how someone’s digital footprint is created, we created some fake personas. We used the website Fake Name Generator to generate a name for our fake people. We then proceeded to create social media accounts on Facebook, Instagram, and Tumblr. We all started with different Android devices which included a Nokia 2 with Android version 7.1.1 installed, a Model TA-1035 Samsung phone with Android version 4.1.2, and finally a Samsung Galaxy G6 with Android version 7.0. After creating our fake accounts, we generated data on each one. For the data generation, we would try to emulate how a real user would use social media by liking, commenting, and reblogging on relevant posts. For each of our accounts, we would follow a particular interest. An example would be one of the accounts that have an interest in chickens. They have a profile picture with a rooster, their bio includes their love for poultry care, and finally, this user likes, follows, and comments on other accounts related to chickens. As well as doing all this testing, we researched the algorithms that Instagram, Facebook, and Tumblr use for recommending posts and ads. As of now, our team is in the middle of the project, continuing to generate data and develop our research on the footprint one leaves behind.
At the beginning of our research, we decided we wanted to understand the deletion process of Tumblr, Instagram, and Facebook. It was hard to find information on this, but we plan on testing this by the last week of the semester. We also have shared posts with each other and other messages to test this. We are generating more posts based on our interests, and then we are going to delete the posts near the end of the semester. We want to know if they still affect the algorithm in some way, and we also want to know how much of the footprint is still left behind after the deletion of the data.