Consolidating user data from social networks using Machine Learning and Serverless Cloud
Alex Kaplunovich, Sophia Kaplunovich · 2023
Social Networks are integral part of our lives. Each of them has application programming interface (API) to access its data. People willingly store their private information, photos, thoughts and locations in numerous forums. We decided to determine how much information we could obtain about a person using automatic cloud serverless architectures, social network’s APIs and advanced Data Science models and algorithms. The paper shows how vulnerable privacy is and how easy it is to consolidate users’ information using modern cloud technologies. We were able to obtain geolocations, friends, similar profiles, predict influencers, and even predict missing friends using Machine Learning graph models. At the end of the day, people should always guard their private information and innovative social platform corporations should carefully think about what data could be given to third parties.