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This workshop aims to bridge disciplines in analyzing text as social and cultural data by addressing methodological challenges in NLP/ML, humanities, and social sciences. Participants will learn about selection bias, annotation bias, model bias, and design bias in the context of studying social and cultural phenomena using large-scale text data. The teaching method involves exploring these biases and discussing the implications for research methodologies. This workshop is intended for researchers and practitioners interested in the intersection of NLP, machine learning, humanities, and social sciences.