Time shifting word2vec models from Times

Time-shifting word2vec models based on Times news paper. These models were generated using the "Generate time shifting models" scripts found here.

In summary, these scripts generate a collection of sentences for every 2 years period, and trains a word2vec model on this period using gensim. The original text from the Times news paper articles is processed as follows:

Articles are divided into sentences using punctuation.

Punctuation symbols are removed.

Text is converted to lower case.

Word are validated to ensure they are valid English non-stop words (using nltk).

The two year time period was selected following the Measure convergence for a range described here.

This data publication was made possible thanks to collaboration with the Utrecht Digital Humanities Lab.

Unfortunately original Times data set is not publicly available.