Deep Mind: Leveraging Deep Learning to Classify and Interpret Mind Perception in Smart Objects From Unstructured Text
This research proposes a novel methodological approach to automated text analysis. We train a state-of-the-art deep contextual language model to classify mind perception from unsolicited, consumer-generated text and use manifold methods to provide a rich set of interpretable linguistic features that shed new light on consumer-smart object relationships.
Citation:
Anouk Bergner, Jochen Hartmann, and Christian Hildebrand (2021) ,"Deep Mind: Leveraging Deep Learning to Classify and Interpret Mind Perception in Smart Objects From Unstructured Text", in NA - Advances in Consumer Research Volume 49, eds. Tonya Williams Bradford, Anat Keinan, and Matthew Matthew Thomson, Duluth, MN : Association for Consumer Research, Pages: 416-417.
Authors
Anouk Bergner, University of St. Gallen, Switzerland
Jochen Hartmann, University of Hamburg
Christian Hildebrand, University of St. Gallen, Switzerland
Volume
NA - Advances in Consumer Research Volume 49 | 2021
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