Dialect topic modeling

This repo contains scripts and metadata for the paper "Corpus-based dialectometry with topic models". For the original data, see below. There are two scripts: one for pre-processing your data to character n-grams, and one for the actual topic modeling. For Morfessor-segmentation, please refer to https://morfessor.readthedocs.io/en/latest/general.html.

• ngramming.py assumes your data is stored in a folder as txt files. You can run the script by

python3 ngramming.py your-corpus-name

This will result in four json files: words_corpus, bigram_corpus, trigram_corpus and fourgram_corpus.

• dialectTopicModel.py assumes your data is stored in the aforementioned json files. There are several arguments one can change in the running of the model.

Example runs of the topic model

• 5-component model of SKN on bigrams and NMF

dialectTopicModel.topic_model('skn', 'bigram', 'skn_bigram', 'nmf', 5, use_idf=True, norm='l2', sublinear=True)

• 2-component model of Archimob on words and LDA

dialectTopicModel.topic_model('archimob', 'words', 'archimob_words', 'lda', 2, relevance=True, lambda_=0.2)

Original paper data

• Samples of Spoken Finnish: https://korp.csc.fi/download/SKN/skn-vrt/
• Norwegian Dialect Corpus: http://www.tekstlab.uio.no/scandiasyn/download.html
• Archimob Corpus of Swiss German: https://spur.uzh.ch/en/departments/research/textgroup/ArchiMob.html