Beyond the binary? Automated gender classification of social media profiles

This paper discusses automated gender classification for social media profiles. It focuses on epistemological and methodological issues that researchers need to consider when using gender classification techniques. It begins with an examination of the category of gender from a queer feminist perspective in the first part. The second part discusses decision points and their potential impact on results at different stages of the research process: From identifying the research angle, to choosing a method, to analysis and validation, to reporting results. Several existing approaches are critically discussed. In the third part, an empirical case study is presented that follows a multi-step procedure of gender classification that aims to overcome a binary gender logic using different methods, such as dictionaries of gendered attributes and personal pronouns, as well as name-gender-inference. By reflecting on the challenges of each step of the analysis, the procedure follows an approach of discrimination-aware data analysis, which can be conceptualized as a form of intervention within the context of queer data practices.