Paper Info
Title
The linguistic construal of disciplinarity: A data‐mining approach using register features
Abstract
We analyze the linguistic evolution of selected scientific disciplines over a 30-year time span (1970s to 2000s). Our focus is on four highly specialized disciplines at the boundaries of computer science that emerged during that time: computational linguistics, bioinformatics, digital construction, and microelectronics. Our analysis is driven by the question whether these disciplines develop a distinctive language use-both individually and collectively-over the given time period. The data set is the English Scientific Text Corpus (SCITEX), which includes texts from the 1970s/1980s and early 2000s. Our theoretical basis is register theory. In terms of methods, we combine corpus-based methods of feature extraction (various aggregated features [part-of-speech based], n-grams, lexico-grammatical patterns) and automatic text classification. The results of our research are directly relevant to the study of linguistic variation and languages for specific purposes (LSP) and have implications for various natural language processing (NLP) tasks, for example, authorship attribution, text mining, or training NLP tools.
Year
DOI
Venue
2016
10.1002/asi.23457
JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY
Keywords
Field
DocType
data mining,automatic classification
Data mining,Text mining,Information retrieval,Computer science,Computational linguistics,Text corpus,Feature extraction,Attribution,Construal level theory,Natural language processing,Artificial intelligence,Linguistics
Journal
Volume
Issue
ISSN
67
7
2330-1635
Citations 
PageRank 
References 
2
0.66
13
Authors
5
Name
Order
Citations
PageRank
Elke Teich17719.09
Stefania Degaetano-Ortlieb275.86
Peter Fankhauser317114.88
Hannah Kermes4246.42
Ekaterina Lapshinova-Koltunski5137.67