12K Finding Wisdom in the Consumer Crowd – Exploring Online Comments Via Content Analysis and Automated Classification Using Deep Neural Networks For Semantic Similarity

We conduct a content analysis of online consumer comments on organic food and reproduce its results with automated text analysis based on a deep pre-trained neural network model for semantic similarity. We find that small-scale consumer research can inform zero-shot machine learning algorithms to analyze opinions in larger datasets.



Citation:

Hannah Danner, Gerhard Hagerer, Florian Kasischke, and Georg Groh (2019) ,"12K Finding Wisdom in the Consumer Crowd – Exploring Online Comments Via Content Analysis and Automated Classification Using Deep Neural Networks For Semantic Similarity", in NA - Advances in Consumer Research Volume 47, eds. Rajesh Bagchi, Lauren Block, and Leonard Lee, Duluth, MN : Association for Consumer Research, Pages: 965-965.

Authors

Hannah Danner, Technical University of Munich, Germany
Gerhard Hagerer, Technical University of Munich, Germany
Florian Kasischke, Technical University of Munich, Germany
Georg Groh, Technical University of Munich, Germany



Volume

NA - Advances in Consumer Research Volume 47 | 2019



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