Text as Data is an interdisciplinary field that focuses on extracting valuable insights from large volumes of textual information. Using computational techniques, such as natural language processing, machine and deep learning, it aims to convert unstructured text into actionable knowledge. As a part of this group, we develop algorithms and tools to process, categorize, and derive meaning from textual content, enabling applications in sentiment analysis, information retrieval, and text mining. Text as Data is crucial for understanding patterns, trends, and sentiments present in vast amounts of textual data, offering valuable applications in health, economics, education, sustainability and various other fields of research.
Faculty doing this research
Sunandan Chakraborty
Angela P Murillo
Saptarshi Purkayastha
Ming Jiang
Examples of projects
Mining causal relationships from text
A Community-Inclusive AI Chatbot to Support Teachers in Developing Culturally-Aware STEM Activities
AI-based Approach to Facilitate Code-Switching for AAVE Speaking Students