Moral Embeddings: A closer look at their Performance, Generalizability and Transferability

Moral values are abstract ideas that ground our judgements towards what is right or wrong. However, with the rapid unfold of moral rhetoric on social media, it becomes increasingly important to place these ideas in a moral frame, contain their harmful effects, and recognise their positive ones. So far, estimating values from opinionated text has...

Active Learning To Reduce Human Labeling For Automatic Psychological Text Classification

In recent years there has been an increase in the number of patients for issues relating to mental illness. To this effect to help with this increase, schema mode assessment through a conversation agent is being used to conduct schema therapy, a form of psychological treatment. To train such an agent, training data labeled by humans is necessary...

Extracting location context from transcripts: a comparison of ELMo and TF-IDF

Using transcripts of the TV-series FRIENDS, this paper explores the problem of predicting the location in which a sentence was said. The research focuses on using feature extraction on the sentences, and training a logistic regression model on those features. Specifically looking at the differences in performance between using ELMo and TF-IDF...

Using Skip-Gram Model to Predict from which Show a Given Line is

Text classification has a wide range of usage such as extracting the sentiment out of a product review, analyzing the topic of a document and spam detection. In this research, the text classification task is to predict from which TV-show a given line is. The skip-gram model, originally used to train the Word2Vec sentence embeddings [Mikolov et...