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035   $a(oapen)https://directory.doabooks.org/handle/20.500.12854/37952
035   $a(PPN)243699654
035   $a(EXLCZ)994100000010106035
100   $a20211214i20192020  uu 
101 0 $aeng
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181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 00$aInformation-theoretic causal inference of lexical flow$fJohannes Dellert
210   $aBerlin$cLanguage Science Press$d2019
210  1$aBerlin :$cLanguage Science Press,$d2019.
215   $a1 online resource (1 p.)
225 1 $aLanguage Variation
311   $a3-96110-144-2 
330   $aThis volume seeks to infer large phylogenetic networks from phonetically encoded lexical data and contribute in this way to the historical study of language varieties. The technical step that enables progress in this case is the use of causal inference algorithms. Sample sets of words from language varieties are preprocessed into automatically inferred cognate sets, and then modeled as information-theoretic variables based on an intuitive measure of cognate overlap. Causal inference is then applied to these variables in order to determine the existence and direction of influence among the varieties. The directed arcs in the resulting graph structures can be interpreted as reflecting the existence and directionality of lexical flow, a unified model which subsumes inheritance and borrowing as the two main ways of transmission that shape the basic lexicon of languages.
410   $aLanguage Variation
606   $aLinguistics$2bicssc
610   $aLinguistics
615  7$aLinguistics
700   $aDellert$b Johannes$0916718
801  0$bScCtBLL
801  1$bScCtBLL
906   $aBOOK
912   $a9910367571103321
996   $aInformation-theoretic causal inference of lexical flow$92055171
997   $aUNINA