Language Change Quantification Using Time-separated Parallel Translations.

We introduce a systematic approach to language change quantification by studying unconsciously used language features in time-separated parallel translations. For this purpose, we use objective style markers such as vocabulary richness and lengths of words, word stems and suffixes, and employ statis...

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Published in:Literary & Linguistic Computing Vol. 22; no. 4; pp. 375 - 394
Main Authors: Altintas, Kemal, Can, Fazli, Patton, Jon M.
Format: Article
Published: Oxford University Press / USA Nov2007
Subjects:
Online Access:View this record in EBSCOhost
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      dt: Nov2007
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      pub: Oxford University Press / USA
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        10.1093/llc/fqm026
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        atl: Language Change Quantification Using Time-separated Parallel Translations.
      aug:
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          Altintas, Kemal
          Can, Fazli
          Patton, Jon M.
        affil:
          Computer Science Department, University of California, Irvine, Irvine, CA 92612, USA
          Computer Science and Systems Analysis Department, Miami University, Oxford, OH 45056, USA
          Information Technology Services, Miami University, Oxford, OH 45056, USA
      su:
        Language & languages
        Vocabulary
        Translations
        Lexicology
        Linguistics
        Loanwords
        Ethnology
        Anthropology
        Lexicon
      sug:
        subj:
          Language & languages
          Vocabulary
          Translations
          Lexicology
          Linguistics
          Loanwords
          Ethnology
          Anthropology
          Lexicon
      ab: We introduce a systematic approach to language change quantification by studying unconsciously used language features in time-separated parallel translations. For this purpose, we use objective style markers such as vocabulary richness and lengths of words, word stems and suffixes, and employ statistical methods to measure their changes over time. In this study, we focus on the change in Turkish in the second half of the twentieth century. To obtain word stems, we first introduce various stemming techniques and show that they are highly effective. Our statistical analyses show that over time, for both text and lexicon, the length of Turkish words has become significantly longer, and word stems have become significantly shorter. We also show that suffix lengths have become significantly longer for types and the vocabulary richness based on word stems has shrunk significantly. These observations indicate that in contemporary Turkish one would use more suffixes to compensate for the fewer stems to preserve the expressive power of the language at the same level. Our approach can be adapted for quantifying the change in other languages.
      pubtype: Academic Journal
      doctype: Article
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    language: English
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