Bio: Maria Antoniak is a PhD candidate in Information Science at Cornell University. Her research focuses on unsupervised natural language processing methods and applications to computational social science and cultural analytics. Her work translates methods from natural language processing to insights about communities and self-disclosure by modeling personal experiences shared in online communities. She has a master’s degree in computational linguistics from the University of Washington and a bachelor’s degree in humanities from the University of Notre Dame, and she has completed research internships at Microsoft, Facebook, Twitter, and Pacific Northwest National Laboratory.
Talk Title: Modeling Personal Experiences Shared in Online Communities
Talk Abstract: Written communications about personal experiences—and the emotions, narratives, and values that they contain—can be both rhetorically powerful and statistically difficult to model. The first goal of my research is to use natural language processing methods to represent complex personal experiences and self-disclosures communicated in online communities. Two fruitful sites for this research are online communities grounded in structured cultural experiences (books, games) and online communities grounded in healthcare experiences (childbirth, contraception, pain management). These communities situate personal opinions and stories in social contexts of reception, expectation, and judgment. The second goal of my research is critical re-examination of measurement methods: I probe models designed for traditional natural language processing tasks involving large, generic datasets by exploring their results on small, socially-specific datasets that are popular in cultural analytics and computational social science.