Splits or waves? Trees or webs? How divergence measures and network analysis can unravel language histories

Paul Heggarty, Warren Maguire, April Mary McMahon

Research output: Contribution to journalArticlepeer-review

60 Citations (SciVal)

Abstract

Linguists have traditionally represented patterns of divergence within a language family in terms of either a ‘splits’ model, corresponding to a branching family tree structure, or the wave model, resulting in a (dialect) continuum. Recent phylogenetic analyses, however, have tended to assume the former as a viable idealization also for the latter. But the contrast matters, for it typically reflects different processes in the real world: speaker populations either separated by migrations, or expanding over continuous territory. Since history often leaves a complex of both patterns within the same language family, ideally we need a single model to capture both, and tease apart the respective contributions of each. The ‘network’ type of phylogenetic method offers this, so we review recent applications to language data. Most have used lexical data, encoded as binary or multi-state characters. We look instead at continuous distance measures of divergence in phonetics. Our output networks combine branch- and continuum-like signals in ways that correspond well to known histories (illustrated for Germanic, and particularly English). We thus challenge the traditional insistence on shared innovations, setting out a new, principled explanation for why complex language histories can emerge correctly from distance measures, despite shared retentions and parallel innovations.
Original languageEnglish
Article number1559
Pages (from-to)3829-3843
Number of pages15
JournalPhilosophical Transactions B: Biological Sciences
Volume365
DOIs
Publication statusPublished - Dec 2010

Keywords

  • tree
  • network
  • phylogeny
  • historical lingusitics
  • language history
  • language divergence

Fingerprint

Dive into the research topics of 'Splits or waves? Trees or webs? How divergence measures and network analysis can unravel language histories'. Together they form a unique fingerprint.

Cite this