Researching Algorithms and Recommendation Systems Inside Out Using Reversed Engineering

It is difficult for a lone researcher to obtain an unfiltered perspective of algorithms in digital media and recommendation systems platforms because these companies tend be reluctant share insights into their business models. Researchers therefore need develop new methods knowledge. The method reversed engineering, which explores algorithm from the inside out by “re-engineering” how are set up, has been recommended gaining empirical knowledge about work what they do. This paper uses engineering illustrate dating calculate matches between single persons. One findings that matching follows psychological discourse based on similarities personality other personal aspects candidates when recommending matches, thus ignoring socioeconomic principles (e.g. economic income, social class, educational level) science find important choosing life-long partnership. Another observation algorithmic machinery ‘more same’ logic, risks limiting pool user gain access to.