Social media are becoming more and more popular and are used to discuss a wide range of topics. On these platforms we are often experiencing polarization between the users, producing a clear separation between groups with different opinions. Echo Chambers are closely related to this phenomenon: an Echo Chamber is a group of users with the same beliefs that reinforce their ideas. The growing complexity and quantity of online interactions requires us to find new techniques for detecting Echo Chambers. In this work we propose the Echo Chamber Problem (ECP) and the Densest Echo Chamber Problem (D-ECP), new formulations that take into account the concepts of content (the piece of information that is discussed) and thread (the "locality" discussing the content) in finding polarization.