Review published In: Register Studies
Vol. 2:1 (2020) ► pp.166–171
Book review
Biber, D. & Egbert, J. (2018). Register variation online
Reviewed by
Published online: 10 April 2020
https://doi.org/10.1075/rs.19018.smi
https://doi.org/10.1075/rs.19018.smi
Article outline
- 1.Introduction
- 2.Summary of chapters
- 3.Evaluation
- 3.1Methodological contribution 1: Using Mechanical Turk to recruit end users to classify web texts
- 3.2Methodological contribution 2: Developing new keyword and key feature methodologies
- 3.3Implication for future studies of internet language
References
References (7)
Biber, D., & Egbert, J. (2016). Register variation on the searchable web: A multi-dimensional analysis. Journal of English Linguistics, 44(2), 95–137.
Biber, D., Egbert, J., & Davies, M. (2015). Exploring the composition of the searchable web: A corpus-based taxonomy of web registers. Corpora, 10(1), 11–45.
Chris (2019, November 18). Writer who never learned to drive works for Uber. Makes $0.97/hr. [Blog post]. Retrieved from: <[URL]> (3 December, 2019).
Davies, M. (2013). Corpus of Global Web-Based English: 1.9 billion words from speakers in 20 countries (GloWbE). Retrieved from: <[URL]> (3 December, 2019).
Egbert, J., & Biber, D. (2019). Incorporating text dispersion into keyword analyses. Corpora, 14(1), 77–104..
Egbert, J., Biber, D., & Davies, M. (2015). Developing a bottom-up, user-based method of web register classification. Journal of the Association for Information Science and Technology, 66(9), 1817–1831.
Newman, A. (2019, November 15). I found work on an Amazon website. I made 97 cents an hour. The New York Times. Retrieved from: <[URL]> (3 December, 2019).