TextXD - Text Analysis Across Domains

TextXD brings together researchers from across a wide range of disciplines, who work with text as a primary source of data, whether they identify as computer, social, data, or information scientists, including linguists. We work to identify common principles, algorithms and tools to advance text-intensive research, and break down the boundaries between domains, to foster exchange and new collaborations among like-minded researchers. TextXD seeks to facilitate mutually beneficial collaborations by hosting natural language processing (NLP) groups activities, including semesterly symposia to surface common NLP problems and new opportunities for cross-disciplinary collaboration.

TextXD holds annual meetings, the presetations and tutorials from which are available via these links:

Register now for TextXD 2019, which will be held at UC Berkeley on December 3-6, 2019, bringing together researchers from across a wide range of disciplines, who work with text as a primary source of data. 

BIDS Affiliates

Leader

Chris Kennedy

Biostatistics

Heather Haveman

Sociology, Haas School of Business, UC Berkeley