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Automatically identifying blend splinters that are morpheme candidates
- Source :
- Digital Scholarship in the Humanities. 31:55-71
- Publication Year :
- 2014
- Publisher :
- Oxford University Press (OUP), 2014.
-
Abstract
- Forms such as -topia in privatopia or -ercise in dancercise are known as blend splinters: they might not be morphemes, but they are clearly involved in word formation. This article offers an automated method that can highlight blend splinters which have the potential to become morphemes in their own right. For instance, the word alcoholic has given rise a large number of blends such as workaholic or rageaholic , so that the splinter -holic is now recognized as a morpheme in the Oxford English Dictionary Online. Because of the sheer number of newly coined blends, it is difficult to identify splinters that are turning into morphemes on the sole basis of human observation. It would therefore be desirable to have an automated method that could process large amounts of data and identify such elements. This article develops such a method, relying on unsupervised morphological segmentation (Harris, 1955). A custom blend database was established for this purpose. The method is able to detect splinters mentioned in previous research, such as -tainment , -ercise , and cyber- , but in addition, it also detects elements that have not been discussed so far, including -tastic , -sumer , and -verse .
- Subjects :
- 060201 languages & linguistics
Linguistics and Language
business.industry
Computer science
06 humanities and the arts
Word formation
computer.software_genre
Language and Linguistics
Computer Science Applications
Morpheme
0602 languages and literature
Artificial intelligence
business
Morphological segmentation
computer
Word (computer architecture)
Natural language processing
Information Systems
Automated method
Subjects
Details
- ISSN :
- 2055768X and 20557671
- Volume :
- 31
- Database :
- OpenAIRE
- Journal :
- Digital Scholarship in the Humanities
- Accession number :
- edsair.doi...........d6ef94bb429debfbdd5c3d7bc3f89f3f
- Full Text :
- https://doi.org/10.1093/llc/fqu059