Sharing stories with one another is a compelling form of communication and the way in which stories are
organized helps to give a larger meaning to facts and events in text. We are developing methods to model
narrative style and the collective building of narratives on social media in order to provide a larger
contextual background for individual posts, as well as gaining a richer understanding of the stories that
people are sharing and their effects on others.
Sarcasm, Humor And Slang In Online Communication
The text that people write online in informal settings often contains features that cause problems to traditional
NLP pipelines, such as sarcasm, humor, and slang. We are working to develop new datasets, methods, and tools
that enable better semantic representations of this type of text to both improve our NLP models and to better
understand these phenomena and the people that use them in their writing.
Online Harms And Misinformation
We are focused on applying our NLP methods to helping to make the internet a safer place. This includes using
computational approaches to detecting, characterizing, and combating offensive language, bias, and misinformation
that is common in online text-based datasets.
Personal Values And Human Activities
The things that people choose to talk about are, in some ways, a reflection of what is important to them.
We explore how language use is connected to personal values, which are, in turn, connected to what people
choose to do. Using data from free-response surveys and social media, we build models and lexical resources
for the measurement of personal values in text.