Document Type
Conference Proceeding
Publication Date
9-2016
Journal Title
2016 Proceedings of the 34th ACM International Conference on the Design of Communication
ISBN
978-1-4503-4495-1
DOI
10.1145/2987592.2987603
Abstract
This paper reports on the results of an intensive application development workshop held in the summer of 2015 during which a group of thirteen researchers came together to explore the use of machine-learning algorithms in technical communication. To do this we analyzed Amazon.com consumer electronic product customer reviews to reevaluate a central concept in North American Genre Theory: stable genre structures arise from recurring social actions. We discovered evidence of genre hybridity in the signals of instructional genres embedded into customer reviews. Our paper discusses the creation of a prototype web application, "Use What You Choose" (UWYC), which sorts the natural language text of Amazon reviews into two categories: instructionally-weighed reviews (e.g., reviews that contain operational information about products) and non-instructionally-weighed reviews (those that evaluate the quality of the product). Our results contribute to rhetorical genre theory and offer ideas on applying genre theory to inform application design for users of information services.
First Page
1
Last Page
8
Num Pages
8
Publisher
Association for Computing Machinery
Recommended Citation
Brian N. Larson, William Hart-Davidon, Kenneth C. Walker, Douglas M. Walls & Ryan Omizo,
Use What You Choose: Applying Computational Methods to Genre Studies in Technical Communication,
1
(2016).
Available at:
https://scholarship.law.tamu.edu/facscholar/831
File Type
Included in
Gender, Race, Sexuality, and Ethnicity in Communication Commons, Law Commons, Other Communication Commons