Geographic Disaggregation of Textual Social Media Data: A Machine Learning-based Approach

This research aims to identify the geographic origin of Arabic-speaking social media users by analyzing textual data they produce and share. The paper presents an approach to infer users’ region (i.e country) of origin through identification of the dialect they use in their written interactions. An Integrated Dataset for Arabic Dialect Detection (IADD) is proposed and used to train multiple classifiers which succeed in identifying the users’ region and country of origin with an accuracy of 0.89 and 0.93, respectively.