The Roe v. Wade sentence: an analysis of tweets trough Symmetric Non-Negative Matrix Factorization

In recent years, social media has become the main field for sourcing textual data. In particular, mi croblogging platforms such as Twitter make it possible to study users' online discussions by understanding and analysing the opinions, comments, and experiences that users share on different issues. One of the most debated issues in recent years is the voluntary termination of pregnancy. In particular, the United States Supreme Court's Roe v. Wade ruling has brought the abortion debate back to the forefront. Indeed, after the annulment of the ruling that restricted the right to abortion in the U.S., the response of online users has been crucial. Indeed, the aim of the paper is to understand what the major topics of discussion have been in the wake of the ruling. To do this, semantic clusters of terms were created through a symmetrical matrix reduction technique, Symmetric Non-Negative Matrix factorization.