The training data in the model contains 20K instances: 10K instances of target word, 10K auxiliary instances.
we used the JGibbLDA 1 framework for topic model estimation and inference, and examined the following LDA parameters: number of topics K, dirichlet hyperparameters for document-topic distribution α and topic-term distribution β.