The rapid growth of social media in recent years has fed into some highly undesirable
phenomena such as proliferation of hateful and offensive language on the Internet. Previous …

Word embeddings are usually derived from corpora containing text from many individuals,
thus leading to general purpose representations rather than individually personalized …

In this paper, we introduce personalized word embeddings, and examine their value for
language modeling. We compare the performance of our proposed prediction model when …

The spread of hate speech (HS) in the digital age poses significant challenges, with online
platforms becoming breeding grounds for harmful content. While many natural language …

The rapid growth of social media in recent years has fed into some highly undesirable
phenomena such as proliferation of abusive and offensive language on the Internet …

When people verbalize what they have felt with different sensory functions, they often
represent different meanings such as with temperature range using the same word cold or …

This thesis focuses on personalization, word representations, and longitudinal dialog. We
first look at users expressions of individual preferences. In this targeted sentiment task, we …

Natural language processing (NLP) involves automatically analyzing text written by human
authors. People develop their own use of a language known as an idiolect, which could …