  This paper discusses creating and analysing a new dataset for data mining and
text analytics research, contributing to a joint Leeds University research
project for the Corpus of National Dialects. This report investigates machine
learning classifiers to classify samples of French dialect text across various
French-speaking countries. Following the steps of the CRISP-DM methodology,
this report explores the data collection process, data quality issues and data
conversion for text analysis. Finally, after applying suitable data mining
techniques, the evaluation methods, best overall features and classifiers and
conclusions are discussed.
