Kathleen R. McKeown’s interest lie in the areas of natural language process, summarization, natural language generation, and social media. Her research interests include text summarization, natural language generation, multi-media explanation, question-answering, and multi-lingual applications. Currently, her group is working in three main areas: text summarization of disaster updates, personalized messaging to help reduce energy use, and identifying sentiment in social media posts.
McKeown’s work on disaster updates makes use of live, streaming information over each hour in the course of a disaster. This project incorporates personal experiences of those who have lived through a disaster, thus providing both an objective and personal point of view.
In the realm of social media, she has previously developed systems to identify influence in social media and to identify an author's personal traits. She is now working on identifying sentiment in social media posts made in low resource languages (e.g., Uyghur) and on identifying aggression and loss in posts from gang-involved youths from Chicago.