Classification of Serbian texts based on lexical characteristics and multivariate statistical analysis
Bibliographic Data
| ID | 19499138 |
|---|---|
| Authors | Peter Zörnig (0000-0002-1094-3972, Universidade de Brasília), Emmerich Kelih (0000-0002-8315-8916, Institut für Slawistik, Universität Wien, Spitalgasse 2, Hof 3, A-1090 Wien, corresponding author), Ladislav Fuks |
| Year | 2016 |
| Volume | 7 |
| Issue | 1 |
| Pages | 41-66 |
| Publication date | 2016-06-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Glottotheory (JOURNAL) |
| Journal identifiers | ISSN: 1337-7892 • E-ISSN: 2196-6907 |
| Publisher | Walter de Gruyter GmbH (PUBLISHER • DE) |
| DOI | 10.1515/glot-2016-0004 |
| OpenAlex | W2440929863 |
| Language | EN |
| References cited | 11 |
We study lexical properties of different Serbian text types (poems, rock songs, different kinds of spoken language, prose, scientific and journalistic texts). We investigate characteristics and text parameters based on the frequency of word forms (relative frequencies, repeat rate, h-point and related indices). Relations between parameters are studied in order to identify the principal characteristics. We also apply techniques of multivariate analysis (cluster analysis, MDS) to classify the text types adequately. One additional objective of the present paper is to illustrate the functioning of these techniques in detail by explicit calculations of all programming steps
Linguistics · Multivariate analysis · Multivariate statistics · Natural language processing · Serbian · Statistics · Advanced Text Analysis Techniques · Authorship Attribution and Profiling · Computer Science · Mathematics · Philosophy · Text Readability and Simplification · Artificial Intelligence
| Highly cited | No |
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