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The linguistic construal of disciplinarity: A data‐mining approach using register features
Author(s) -
Teich Elke,
DegaetanoOrtlieb Stefania,
Fankhauser Peter,
Kermes Hannah,
LapshinovaKoltunski Ekaterina
Publication year - 2016
Publication title -
journal of the association for information science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.903
H-Index - 145
eISSN - 2330-1643
pISSN - 2330-1635
DOI - 10.1002/asi.23457
Subject(s) - computer science , register (sociolinguistics) , natural language processing , artificial intelligence , computational linguistics , linguistics , clef , focus (optics) , set (abstract data type) , corpus linguistics , feature (linguistics) , task (project management) , philosophy , physics , programming language , management , optics , economics
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 E nglish S cientific T ext C orpus ( 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.