In this Master Thesis project, the objective is to study how can Supervised Machine Learning be used to detect text-based rumours for humanitarian activities in Twitter. A model was developed in this project in order to classify a tweet at question whether is a rumour or not and whether is relevant to humanitarian activities or not. The findings of this research were promising as the classification modules developed were able to score 75.8% in Recall classifying tweets to rumours and non-rumours and 96.6% in Recall classifying tweets to relevant to humanitarian activities and not relevant.