For statisticians, traditional methods such as data mining, hypothesis testing, and inference have long been the backbone of analysis. These approaches remain powerful, but new tools—especially natural language processing and generative AI—make it easier to uncover insights, automate text-heavy tasks, and support decision-making at scale.
natural language processing
Workshop Focuses on Role of Statistics in LLM Era
The Columbia University Department of Statistics, New York City Metro Area Chapter of the ASA, and ASA Section on Text Analysis sponsored a workshop on large language models during which participants had an in-depth conversation about the roles of statistics in an era of LLMs—not only the opportunities for statistical innovations, but also the potential risks.
TAIG Contest Winners Tell of Experience
During JSM 2020, ASA Text Analysis Interest Group award committee members systematically evaluated a large body of research in the growing field of text analysis and presented awards to Qiuyi Wu and Enshuo Hsu for theirs.
Text Analysis Interest Group Recaps First Full Year
The ASA’s Text Analysis Interest Group (TAIG) has had a productive first full year. TAIG brings together individuals and groups who have an active interest in text analysis, text mining, natural language processing, and related areas of research at their intersection with statistics.
New ASA Interest Group: Text Analysis
The ASA’s big tent grew bigger recently with the addition of the Text Analysis Interest Group (TAIG). The group was petitioned in the fall of 2018 and formally approved by the Council of Sections Executive Committee in March 2019.
Making a Statistical Impact with Text Data
ASA President Karen Kafadar discusses how statistics can be used to find solutions for the challenge of text data.