Identifying User Interests In An Online Discussion Forum With Deep Learning

The probabilistic topic model Latent Dirichlet Allocation (LDA) was deployed to model the themes of discourse in discussion threads on the social media aggregation website Reddit. Abstracting discussion threads as vectors of topic weights, these vectors were fed into several neural network architectures, each with a different number of hidden layers, to train machine learning models that could identify which discussion would be of interest for a given user to contribute. Using accuracy as the evaluation metric to determine which model framework achieved the best performance on a given user’s validation set, these selected models achieved an average accuracy of 66.1% on the test data for a sample set of 30 users. Using the predicted probabilities of interest made by these neural networks, recommender systems were further built and analyzed for each user.