I Generated 1,000+ Fake Dating Profiles for Data Science

How I used Python Web Scraping to Create Dating Profiles

D ata is one of the world’s newest and most precious resources. Most data gathered by companies is held privately and rarely shared with the public. This data can include a person’s browsing habits, financial information, or passwords. In the case of companies focused on dating such as Tinder or Hinge, this data contains a user’s personal information that they voluntary disclosed for their dating profiles. Because of this simple fact, this information is kept private and made inaccessible to the public.

However, what if we wanted to create a project that uses this specific data? If we wanted to create a new dating application that uses machine learning and artificial intelligence, we would need a large amount of data that belongs to these companies. But these companies understandably keep their user’s data private and away from the public. So how would we accomplish such a task?

Well, based on the lack of user information in dating profiles, we would need to generate fake user information for dating profiles. We need this forged data in order to attempt to use machine learning for our dating application. Now the origin of the idea for this application can be read about in the previous article:

Can You Use Machine Learning to Find Love?

The previous article dealt with the layout or format of our potential dating app. We would use a machine learning algorithm called K-Means Clustering to cluster each dating profile based on their answers or choices for several categories. Also, we do take into account what they mention in their bio as another factor that plays a part in the clustering the profiles. Continue reading “I Generated 1,000+ Fake Dating Profiles for Data Science”