Developing a bottom-up, user-based method of web register classification

Jesse Egbert, Douglas Biber, Mark Davies

Research output: Contribution to journalArticlepeer-review

42 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1817-1831
Number of pages15
JournalJournal of the Association for Information Science and Technology
Issue number9
StatePublished - Sep 1 2015


  • classification
  • discourse analysis
  • linguistic analysis

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications
  • Information Systems and Management
  • Library and Information Sciences


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