Treball de fi de màster en Lingüística Teòrica i Aplicada. Directora: Dra. Núria Bel Rafecas ; Recent decades have seen an increase in the prevalence of the use of computational methods in the study of language, including in sociolinguistics. These methods allow for the study of language variation through the analysis of social media data and even for the mapping of the spread of linguistic variation in the real world. The goal of this study was to assess the utility of computational methods in the extraction of Dutch Low Saxon dialect features from a large Twitter corpus. The results indicate that these dialect features can be used successfully for the training of classifiers and that maps generated based on these features and their associated predictions have the potential to capture the use of Dutch Low Saxon in the Netherlands, although methodological adjustments are advisable for future studies. The study of socioeconomic status as it relates to Low Saxon proved feasible, although to a limited degree.