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International School on Complexity Course on Statistical Physics of Social Dynamics Opinions, Semiotic Dynamics, and Language July 19, 2007. Erice, Italy The Dynamics of Language Evolution [email protected] William S-Y. Wang Chinese University of Hong Kong

International School on Complexity Course on Statistical Physics of Social Dynamics

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International School on Complexity Course on Statistical Physics of Social Dynamics Opinions, Semiotic Dynamics, and Language July 19, 2007. Erice, Italy The Dynamics of Language Evolution [email protected] William S-Y. Wang Chinese University of Hong Kong. - PowerPoint PPT Presentation

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Page 1: International School on Complexity Course on Statistical Physics of Social Dynamics

International School on ComplexityCourse on Statistical Physics of Social DynamicsOpinions, Semiotic Dynamics, and LanguageJuly 19, 2007. Erice, Italy

The Dynamics of Language Evolution

[email protected]

William S-Y. Wang

Chinese University of Hong Kong

Page 2: International School on Complexity Course on Statistical Physics of Social Dynamics

Ma sopra tutte le invenzioni stupende, qual eminenza di mente fu quella di colui che s'immaginò di trovar modo di comunicare i suoi più reconditi pensieri a qualsivoglia altra persona, benché distante per lunghissimo intervallo di luogo e di tempo?

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Languages diversify in

space&

time

Major engines for change:vertical, across generations

horizontal, language contact

Page 4: International School on Complexity Course on Statistical Physics of Social Dynamics

Leonard BloomfieldLanguage

1933

Page 5: International School on Complexity Course on Statistical Physics of Social Dynamics

Cavalli-Sforza, L.L. and W.S-Y.Wang. 1986. Cavalli-Sforza, L.L. and W.S-Y.Wang. 1986. Spatial distance and lexical Spatial distance and lexical replacementreplacement. . LanguageLanguage 62.38-55. 62.38-55.

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Cavalli-Sforza, L.L. and W.S-Y.Wang. 1986.Cavalli-Sforza, L.L. and W.S-Y.Wang. 1986.Spatial distance and lexical replacementSpatial distance and lexical replacement. . LanguageLanguage 62.38-55. 62.38-55.

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“chaque mot a son histoire”

Given the heterogeneous rates of change exhibited by the features of language, including lexical features, how can we capture statistically their distributions, leading to more substantive understanding?

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Meaning : cancellation detour idea acrobatics--------------------------------------------------------------------------------------wago : torikeshi mawarimichi omoitsuki karuwaza和語

kango : kaiyaku ukairo chakusô kyokugei漢語 解 約迂回路 著 想 曲 藝

gairaigo : kyanseru baipasu aidea akurobatto外來語

Lexical strata in JapaneseLexical strata in Japanesebased on Shibatani 1987:133based on Shibatani 1987:133..

Page 9: International School on Complexity Course on Statistical Physics of Social Dynamics

Chinese JapaneseVng=o:

wang 王 o:yang 陽 yo:lang 浪 ro:mang 盲 mo:fang 方 ho:kong 孔 ko:dong 東 to:song 宋 so:nong 農 no:ding 丁 cho:qing 情 jo:xing 星 sho:ming 命 myo:ling 嶺 ryo:bing 冰 hyo:bing 病 byo:

Chinese Japanese

hu 壺 ko h :: khe 鶴 kakuhei 黑 kokuhai 海 kaihua 花 kahua 滑 kotsuhuo 活 katsuhan 漢 kanhun 婚 konhuang 黃 ko:xi 喜 ki h > xxi 系 keixiu 休 kyu:xin 欣 kinxian 險 kenxiang 向 ko:

Page 10: International School on Complexity Course on Statistical Physics of Social Dynamics

• Dao Hua ( 倒话 )– A creole language in

Southwest Sichuan Prov., between the Tibetan area and Han area.

– Emerged 300 years ago during the invasion of Qing troops into Tibetan to suppress the minority riot.

– Influenced a lot by Southwest Mandarin (e.g., Lexicons) and Tibetan (e.g., Grammar).

Dao Hua’s area

ACuo (阿错 )

Page 11: International School on Complexity Course on Statistical Physics of Social Dynamics

Mixture of Mandarin and Tibetan in Dao Hua

– 马 骑 人 一 个 来了。 – Horse ride man one MW come– 一 个 骑 马 的人 来了 .– one MW ride horse Pt man come Pt.

– 他 -ki 茶 喝 -tsv4 - tsu4 - di- jiu3- li 。– he (subject) tea drink (when is going to and not begin yet)– ( 他正要喝茶(还没喝)的时候 )

Mixture in Linguistic components in Dao HuaL: Language; T: Tibetan; M: Mandarin; Z: Dao hua

V: Vocabulary; S: Semantics;

Gc: Grammar (content); Gf: Grammar (form);

Ps: Phonology (Phonotactics ); Pe: Phonology (Phonemes);

L(Z) = {V(M), {Gc(T), Gf(T&M)}, {Ps(M), Pe(T)}, S(T&M)}

Page 12: International School on Complexity Course on Statistical Physics of Social Dynamics

1 ashes belly bird bite all earth 2 bark blood claw burn big I 3 cloud bone dog come black name 4 fire breast feather die cold night 5 leaf ear fish drink dry not 6 man egg horn eat fat one 7 moon eye louse fly full road 8 mountain foot tail give good 9 person hair hear green that 10 rain hand kill long this 11 root head know many thou 12 sand heart lie new two 13 seed knee say red we 14 smoke liver see round what 15 star meat sit small who 16 stone mouth sleep warm 17 sun neck stand white 18 tree nose swim yellow 19 water skin walk 20 woman tongue 21 tooth 100 salt year wind 7 9 5 3 2 9 35

Basic meaningsaccording to

M. Swadesh &S.Yakhontov

Page 13: International School on Complexity Course on Statistical Physics of Social Dynamics

Schleicher, August. Compendium der vergleichenden Grammatikder indo-germanischen Sprachen. 4th ed. 1876. Weimar.

Page 14: International School on Complexity Course on Statistical Physics of Social Dynamics

• Schleicher, August. Compendium der vergleichenden Grammatik der indogermanischen Sprachen. 4th ed. 1876.

• P.8: Die länge der linien deutet die zeitdauer an, die entfernung der selben von einander den verwantschaftsgrad.

• The length of the lines indicates the amount of time which had elapsed and the distance between them degrees of relationship. W.K.Percival 1987:6.

Page 15: International School on Complexity Course on Statistical Physics of Social Dynamics

E G Sw Fr Sp ItGerman Swedish French Spanish Italian Russian

Cognate percentages for basic words.Cognate percentages for basic words.based on Dyen, Kruskal and Black 1992.based on Dyen, Kruskal and Black 1992.

Page 16: International School on Complexity Course on Statistical Physics of Social Dynamics

BJ SZ CS NC MX GZ

Suzhou Changsha Nanchang Meixian Guangzhou Xiamen

Cognate percentages for basic words.Cognate percentages for basic words.based on Xu, 1991.based on Xu, 1991.

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Page 19: International School on Complexity Course on Statistical Physics of Social Dynamics
Page 20: International School on Complexity Course on Statistical Physics of Social Dynamics

Wang, W.S-Y. 1998. Three windows on the past.Pp.508-534 in V.H.Mair, ed.

Page 21: International School on Complexity Course on Statistical Physics of Social Dynamics

William S-Y. Wang.

The migration of the Chinese people and the settlement of Taiwan.

Anthropological Studies of the Taiwan Area 15-36, 1989.

Page 22: International School on Complexity Course on Statistical Physics of Social Dynamics

Two subgroups of equal time depth and retention rate

R

A

W

δ

a b c d w x y z

Page 23: International School on Complexity Course on Statistical Physics of Social Dynamics

a b c d w x y z

a . α α α γ γ γ γ

b . α α γ γ γ γ

c . α γ γ γ γ

d . γ γ γ γ

w . β β β

x . β β

y . β

z .

Page 24: International School on Complexity Course on Statistical Physics of Social Dynamics

a b c d w x y z

a . α α α γ γ γ γ

b . α α γ γ γ γ

c . α γ γ γ γ

d . γ+δ γ γ γ

w . β β β

x . β β

y . β

z .

Suppose language w adopts δ words from language d:

Page 25: International School on Complexity Course on Statistical Physics of Social Dynamics

How can we detect such effects of language contact in prehistory,

• when multiple languages are involved?• when the adoptions are bidirectional?• when the sources are outside the set?

etc.

Page 26: International School on Complexity Course on Statistical Physics of Social Dynamics

Words for integers in some Indo-European languages. from C.Renfrew 1989.

Page 27: International School on Complexity Course on Statistical Physics of Social Dynamics

Vowel alternations in English

a > e e > i i > ai

sanity > sane shepherd > sheep hid > hide

gratitude >grateful kept > keep Christmas > Christ

opacity > opaque serenity > serene divinity > divine

tabular > table obscenity > obscene linear > line

chastity > chaste leapt > leap fifth > five

Page 28: International School on Complexity Course on Statistical Physics of Social Dynamics

pt > tt kt > tt dm > mm dv > vvsettembre ottobre ammirare avversoadattore attore ammettere avverbioadottore *practicare

bd > dd kd > dd ks > ss bs > ssaddome aneddoto affisso assenza*abdicare apoplessia assorbire

assurdo

Page 29: International School on Complexity Course on Statistical Physics of Social Dynamics

Lexical Diffusion - an early modelLexical Diffusion - an early model

UU VV CCWW11 WW11

WW22 WW2 2 ~ ~ WW22

WW33 WW3 3 ~ ~ WW33

.. ,,

.. ..

.. ..

WWnn WWnn

Page 30: International School on Complexity Course on Statistical Physics of Social Dynamics

Lexical Diffusion: [u] > [ŭ] in EnglishLexical Diffusion: [u] > [ŭ] in English

UU VV CC-k-k hookhook

-t-t lootloot sosootot footfoot

-d-d foodfood hoodhood

-m-m gloomgloom grogroomom

-n-n noonnoon

Page 31: International School on Complexity Course on Statistical Physics of Social Dynamics
Page 32: International School on Complexity Course on Statistical Physics of Social Dynamics

Cavalli-Sforza, L.L. & M.W.Feldman. 1981. Cultural Transmission and Evolution. Princeton.

The new word that becomes part of a language, - - -, is an innovation and can be considered as an analog of mutation in biology. - - - When the process of diffusion of an innovation is followed for a sufficiently long time, the frequency of use of the innovation almost always follows an S-shaped curve. At the beginning the number of acceptances rapidly increases - - -. Then follows an approximately linear increase, and finally the increase slows down and is barely perceptible. P.29-30.

Page 33: International School on Complexity Course on Statistical Physics of Social Dynamics

• Shen, Zhongwei. 1997. Exploring the Dynamic Aspect of Sound Change. Journal of Chinese Linguistics Monog. #11.

• Niyogi, Partha, 2006. The Computational Nature of Language Learning and Evolution. MIT Press.

Page 34: International School on Complexity Course on Statistical Physics of Social Dynamics
Page 35: International School on Complexity Course on Statistical Physics of Social Dynamics

Age as Virtual Time

Page 36: International School on Complexity Course on Statistical Physics of Social Dynamics
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Model for Lexical Diffusion — One Word

u

u (1 – c) u c

c

c

t:

t + t:

u + c = 1

u denotes the proportion of unchanged formsc denotes the proportion of changed forms is a constant that controls the rate of change of c, 0 ≤ ≤ 1

Page 38: International School on Complexity Course on Statistical Physics of Social Dynamics

Solution to One Word Model

The frequency of changedforms has the solution:

0 2 4 6 8 10 120

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

t

C (

t)— the Logistic Curve

1e1

e

t

t

tc

Page 39: International School on Complexity Course on Statistical Physics of Social Dynamics

Lexical Diffusion and the Snowball Effect

0 2 4 6 8 10 12 14 16 18 200

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Time

Pro

po

rtio

n o

f w

ord

s t

hat

hav

e ac

qu

ired

ch

ang

ed f

orm

Successive words acquirechanged form at an

increasingly rapid rate

i) in the gradient of curvesi) in the gradient of curves

ii) in the separation of curvesii) in the separation of curves

This can be observed:

Page 40: International School on Complexity Course on Statistical Physics of Social Dynamics

Three examples of linguistic study:

• Lexical replacement in Micronesia,

• Time depth and prehistory,

• Diffusion of a sound change.

Page 41: International School on Complexity Course on Statistical Physics of Social Dynamics

A language is NOT a unitary homogeneous object,

but a heterogeneous, layered, dynamic mosaic of features,

constructed piece-meal by the child during the early years,

and enriched by the adult,

adopting features from other speakers and other languages.

sounds,meanings,words, constructions.etc.

verticaltransmission

horizontaltransmission

Page 42: International School on Complexity Course on Statistical Physics of Social Dynamics

How do we best model the two modes of transmission word by word across the lexicon, from generation to generation, from speaker to speaker, and from community to community?

How do we distinguish the products of the two modes of transmission in order to better understand linguistic prehistory, and thereby human prehistory?

Page 43: International School on Complexity Course on Statistical Physics of Social Dynamics

Cavalli-Sforza, L.L. and W.S-Y. Wang. 1986. Spatial distance and lexical replacement. Language 62.38-55.

Wang, W.S.-Y., J.Y. Ke and J.W. Minett. 2004. Computational studies of language evolution. 65-106 in Computational Linguistics and Beyond. Huang, C.R. and W. Lenders eds. Academia Sinica: Institute of Linguistics.

Gong, T., J. Ke, J.W. Minett, J.H. Holland and W.S-Y. Wang.

2005. Coevolution of lexicon and syntax from a simulation perspective. Complexity, 10.6: 50-62.

Wang, W.S-Y. and J.W. Minett. 2005. Vertical and horizontal transmission in language evolution. Transactions of the Philological Society 103.2.121-46.

Page 44: International School on Complexity Course on Statistical Physics of Social Dynamics

Heartfelt thanks to the two directors,

Luc and Vittorio, and their many able associates

for a week of intellectual feasts on Opinions, Semiotic Dynamics, and Language

in such a fairyland setting !

Grazie di cuore per una settimana stupenda!