Abstract
The recent years have witnessed the development of different computational approaches to the study of linguistic variations and regional dialectology in different languages including English, German, Spanish and Chinese. These approaches have proved effective in dealing with large corpora and making reliable generalizations about the data. In Arabic, however, much of the work on regional dialectology is so far based on traditional methods; therefore, it is difficult to provide a comprehensive mapping of the dialectal variations of all the colloquial dialects of Arabic. As thus, this study is concerned with proposing a computational statistical model for mapping the linguistic variation and regional dialectology in Colloquial Arabic through Twitter based on the lexical choices of speakers. The aim is to explore the lexical patterns for generating regional dialect maps as derived from Twitter users. The study is based on a corpus of 1597348 geolocated Twitter posts. Using principal component analysis (PCA), data were classified into distinct classes and the lexical features of each class were identified. Results indicate that lexical choices of Twitter users can be usefully used for m