Developing a bottom‐up, user‐based method of web register classification. (30th January 2015) - Egbert, Jesse; Biber, Douglas; Davies, Mark
<x xml:space="preserve">Abstract</x> This paper introduces a project to develop a reliable, cost‐effective method for classifying Internet texts into register categories, and apply that approach to the analysis of a large corpus of web documents. To date, the project has proceeded in 2 key phases. First, we developed a bottom‐up method for web register classification, asking end users of the web to utilize a decision‐tree survey to code relevant situational characteristics of web documents, resulting in a bottom‐up identification of register and subregister categories. We present details regarding the development and testing of this method through a series of 10 pilot studies. Then, in the second phase of our project we applied this procedure to a corpus of 53, 000 web documents. An analysis of the results demonstrates the effectiveness of these methods for web register classification and provides a preliminary description of the types and distribution of registers on the web.