Ramírez-Cifuentes D, Freire A. UPF’s Participation at the CLEF eRisk 2018: Early Risk Prediction on the Internet. Conference and Labs of the Evaluation Forum (CLEF2018), ERISK Workshop

This paper describes the participation of the Web Science and Social Computing Research Group from the Universitat Pompeu Fabra, Barcelona (UPF) at CLEF 2018 eRisk Lab1 . Its main goal, divided in two different tasks, is to detect, with enough anticipation, cases of depression (T1) and anorexia (T2) given a labeled dataset with texts written by social media users. Identifying depressed and anorexic individuals by using automatic early detection methods, can provide experts a tool to do further research regarding these conditions, and help people living with them. Our proposal presents several machine learning models that rely on features based on linguistic information, domain-specific vocabulary and psychological processes. The results, regarding the F-Score, place our best models among the top 5 approaches for both tasks