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Germain Gauthier (CREST): "Mining Narratives in Large Text Corpora"
Firms and Markets Seminar
Abstract: When making sense of the world, human beings often rely on narratives: simple, relatable, plausible stories of how the world works. Though these narratives are part of the public and political debate on many policy issues, empirical evidence on their determinants and impact is scarce. This is mainly due to the technical complexity of quantifying narratives. Relying on modern natural language processing techniques, we aim to fill this void and develop an off-the-shelf methodology to identify narratives in large text corpora. We demonstrate the effectiveness of our approach on articles related to taxation in the New York Times over the period 1987-2014, and discuss potential extensions to our methodology.
Joint work with Eliott Ash (ETH Zürich) and Philine Widmer (Univ. St. Gallen)