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Exploring the tiers of Japanese vocabulary: Academic, literary and beyond Tatsuhiko Matsushita LALS, Victoria University of Wellington [email protected]

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Page 1: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Exploring the tiers of Japanese vocabulary: Academic, literary and beyond

Tatsuhiko MatsushitaLALS, Victoria University of Wellington

[email protected]

Page 2: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Main findings• VDRJ is useful for designing curriculum (material, tests etc.)• The more domains a words is shared as AW or LAD by, the more abstract

the meaning of the word is. • Conversation and non-academic texts contain more general words and

LW• Academic texts: more AW and LAD but less LW in any academic domain• Wikipedia: more proper nouns and low frequency words• Newspapers and academic items of Wikipedia can be a good resource

for learning AW and LAD.• Natural science texts contain more academic domain words at lower

frequency levels than arts and social science texts • Origins of academic and literary words are considerably clearly

separated; 3/4 of LW originate in Japanese while 3/4 of AW and LAD originate in Chinese

• LAD contains more Western origin words (Gairaigo)

Page 3: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Contents1. Motive for this research2. Goals of this presentation

3. Vocabulary Database for Reading Japanese4. Tiers of Japanese vocabulary

(Basic words, academic words, limited-academic domain words, literary words)

5. Text coverage by word tier6. Proportions of word origin types by word tiers7. Number of characters required to cover the word tiers

7. Implications from the findings8. Conclusion

Page 4: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

1. Motive for this researchHow efficiently can we learn vocabulary?• Learning burden is big!• More effective choice of target words• More efficient order for learning the words Effective choice and efficient order: to maximize the

coverage of text which the learner would encounter in his/her domain

= Reading comprehension and lexical density (Hu & Nation, 2000; Komori et al., 2004)

Q. What words should learners learn first? And second and next?

Page 5: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Studies on EAP vocabulary

• Basic: General Service List (West, 1953)• Academic: AWL (Coxhead, 2000)        UWL (Xue & Nation, 1984)• EGAP-A/S, EGAP-HM/SS etc.

(Tajino, Dalsky, & Sasao, 2009)• Science-specific Word List (Coxhead & Hirsh, 2007)• Technical: e.g. Chung (2003)• Literary vocabulary?

Page 6: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Studies on JAP vocabulary• Basic: The former JLPT list, Tamamura (1987) etc. • Academic: Butler (2010), Matsushita (2011)• ?• Technical: Komiya (1995), Oka (1992) etc.• Others

• No list for words between academic and technical words• Literary vocabulary?

Page 7: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

2. Goals of this presentationTo introduce I. the Vocabulary Database for Reading JapaneseII. extracted domain-specific words such as Academic

Words (AW), Limited-Academic-Domain Words (LAD), Literary Words (LW)

To argue about IV. how the word tiers work in different types of text

(register variation)V. how learner’s language background possibly

affects the understanding of texts in different genres

Page 8: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

3. Vocabulary Database for Reading Japanese• Vocabulary Database for Reading Japanese ( VDRJ )( Matsushita, 2010; 2011 )• Created from the Balanced Contemporary Corpus of Written

Japanese, 2009 monitor version (NINJAL, 2009)• 33 million token (28 million from books and 5 million from the

Internet forum sites (Yahoo Chiebukuro))• 19 million content words and 14 million function words• Unit of counting: Lexeme – considerably inclusive but less

inclusive than the word family (Level 6 in Bauer & Nation, 1993) in English

• “Short unit of lexemes” are ranked by U (usage coefficient) (Juilland & Chang-Rodrigues, 1964)

• Short unit of lexeme: more inclusive than “lemma”, less inclusive than “word family”

Page 9: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Some problems of existing Japanese word frequency lists

• Lack of representativeness• Too old• The corpus size is not large enough: low reliability for low frequency words• No good sub frequency data which enable us to

calculate dispersion to downgrade unevenly distributed words

Page 10: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Advantages of word lists* Various types of word lists can be created from the vocabulary database (VDRJ)

A) Reference for developing vocabulary tests = Checking learners’ vocabulary levelsB) Reference for checking vocabulary level of material

= Checking vocabulary levels of materials

C) Specify vocabulary for learners to learn and for teachers to teach

For better choice of material, modification of textCf. Nation (2011), Word profiler

Page 11: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

How to make VDRJA) MethodI. Classify all the texts into some sub corpora to see

the range and dispersion cf. Nippon Decimal Classification, BCCWJ (NINJAL, 2009 )

II. Parse (made word segmentation of ) all the texts by a morphological analyzer with a dictionary (if the text is not segmented by space between words.) cf. MeCab, UniDic

III. Make word lists by AntConc and/or AntWordProfiler

Page 12: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Content and construct of VDRJ• Vocabulary Database for Reading Japanese• The list is for reading as it is made from written

corpus of books and internet forum sites• Written and spoken languages are different in word

frequency, domain and required language processing skills ⇒ A good corpus of spoken language is necessary to

develop a good word list for it(, but there is no very good corpus of spoken Japanese…)

Page 13: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

The Classification of Domains and Fields (Corpus form books and internet forum sites, BCCWJ 2009 monitor version)

The tendomains

Code forthe ten

domains

The 28academicfield code

Notes

Literary works LW a6_G All classified as general texts of a6

Humanities and Arts

Languages and Linguistics a1

Philosophy and Religion a2

History a3

Ethnology a4

Fine Arts a5

Literature (non-imaginative texts e.g. critique) a6_T All classified as technical texts of a6

Other Humanities and Arts a7

Social Sciences

Politics s1

Law s2

Economics s3

Commerce and Business s4

Sociology and Social Issues s5 Including welfare, labour, gender issues

Education s6 Including pedagogy on each subject

Other Social Matters s7 Including transportation, media, current issues

Technological Natural Sciences

Mathematics t1

Physics t2

Astronomy, Earth and Planetary Science t3

Chemistry, Metal and Mine t4

Technology (Architecture, Civil Engineering) t5

Technology (Mechanics, Electricity, Marine Engineering) t6

Other Technological Natural Sciences t7Including information science, manufacturing,library science, part of domestic science

Biological Natural Sciences

Biology b1

Agriculture b2Including forestry, fishery, animal husbandry,veterinary

Pharmacy b3

Medicine b4

Dentistry b5

Nursing b6

Other Biological Natural Sciences b7Including sports, hygienics, environmentology,part of domestic science

Internet Q & A Forum (Yahoo Chiebukuro) IF

Domain/Field

Languages,Linguistics and

PhilosophyLP

History andEthnology

HE

Literary Works/Imaginative Texts

STScience andTechnology

Biology andMedicine

BM

AH

Politics andLaw

Economics andCommerce

Sociology,Education andOther Social

Issues

PL

EC

SE

Arts and OtherHumanities

Page 14: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Content of the sub corpora

DomainNumber of

TokensRatio

Literary Works/Imaginative Texts 8251999 25.1%

Languages, Linguistics and Philosophy 2134739 6.5%

History and Ethnology 3336818 10.2%

Arts and Other Humanities 3020917 9.2%

Politics and Law 1881012 5.7%

Economics and Commerce 2209107 6.7%

Sociology, Education and Other Social Issues 2996147 9.1%

Science and Technology 1512784 4.6%

Biology and Medicine 2251037 6.9%

Internet Q & A Forum 5224852 15.9%

Total 32819412 100.0%

Types and Tokens by the Ten Domain Classification(Corpus form books and internet forum sites, BCCWJ 2009monitor version)

Page 15: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Different word rankings

• The word ranking problem mainly exists in Basic Words

• This is mainly due to lack of good spoken corpora

• Compromise: frequency weighted to limited domains which seem to reflect basic daily needs

• For International Students• For General Learners• Non-weighted (ranking for overall written Japanese)

Page 16: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Multidimensional scaling (MDS)

10 domains10 domains

+ word familiarity

Page 17: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

4. Tiers of Japanese vocabulary (1) The concept of “word tiers”• Domain / Level• Level = general importance = frequency × dispersion

Some words are frequent only in a particular domaine.g. 発送 (shipping)  振り込み (paying by bank transfer)  古墳 (tumulus / burial mound)

Page 18: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Assumed word tiers for studentsLevel• Basic: Top 1288 = Former JLPT Level 4 &3• Intermediate: Ranked 1289-5000• Advanced 1: 6K-10K• Advanced 2: 11K-15K • Super-Advanced: 15K-20K• 21K+• Assumed Known Words (AKW)

Domain*General / Academic / Literary

Page 19: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

4. Tiers of Japanese vocabulary (2) Basic words (BW)• Feature of the corpus: formal written language similar to BNC (Nation, 2004)• No good spoken corpus for vocabulary studies• Compromise

• For learners and teachers lists, the former JLPT Level 4 $ 3 vocabulary is put at the top of the list as basic words

To order the basic words• Identify closer domains to word familiarity (basic needs) by

Multidimensional Scaling (MDS)• Frequency in literary works and the Internet-forum sites

(Yahoo-Chiebukuro) is weighted

Page 20: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

4. Tiers of Japanese vocabulary (3) Academic domain words

Extracting academic domain words• Log-likelihood ratio (LLR)(Dunning, 1993)• Target texts: Technical texts

• Classified into four large academic domains• Total number of tokens: approx. 2.9 million

• Reference texts: General texts in BCCWJ 2009• Total number of tokens: approx. 29.9 million

• Extract keywords shared by 4 - 1 domains• Cut off point: higher for more narrowly distributed words

Page 21: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Number of Shared Academic Domains among the 4 academic domains

Ah Ss1 1

22 2

3 3

2 4 2

3 3

Tn Bn

1 2 1

Ah: Arts & Humanities, Ss: Social Sciences,

Tn: Technological Natural Sciences, Bn: Biological Natural Sciences

Page 22: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

4. (3) Academic domain words• Academic words (AW): high specificity in 3+ academic domains

• 4-domain words (cut off point: LLR > 0)• 3-domain words (cut off point: LLR > 0)

• Limited-academic-domain words (LAD)• 2-domain words (cut off point: LLR > 1)• 1-domain words (cut off point: LLR > average value)

• Eliminate the former JLPT Level 4 vocabulary (Top 700 words)• Eliminate the words ranked at 20001 or lower• Classify all the AW and LAD by word ranking levels for

International Students (U=Usage Coefficient): • 5 levels: Basic / Inter. / Adv. 1 / Adv. 2 / Super-adv.

Page 23: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

The Classification of Domains and Fields (Corpus form books and internet forum sites, BCCWJ 2009 monitor version)

The tendomains

Code forthe ten

domains

The 28academicfield code

Notes

Literary works LW a6_G All classified as general texts of a6

Humanities and Arts

Languages and Linguistics a1

Philosophy and Religion a2

History a3

Ethnology a4

Fine Arts a5

Literature (non-imaginative texts e.g. critique) a6_T All classified as technical texts of a6

Other Humanities and Arts a7

Social Sciences

Politics s1

Law s2

Economics s3

Commerce and Business s4

Sociology and Social Issues s5 Including welfare, labour, gender issues

Education s6 Including pedagogy on each subject

Other Social Matters s7 Including transportation, media, current issues

Technological Natural Sciences

Mathematics t1

Physics t2

Astronomy, Earth and Planetary Science t3

Chemistry, Metal and Mine t4

Technology (Architecture, Civil Engineering) t5

Technology (Mechanics, Electricity, Marine Engineering) t6

Other Technological Natural Sciences t7Including information science, manufacturing,library science, part of domestic science

Biological Natural Sciences

Biology b1

Agriculture b2Including forestry, fishery, animal husbandry,veterinary

Pharmacy b3

Medicine b4

Dentistry b5

Nursing b6

Other Biological Natural Sciences b7Including sports, hygienics, environmentology,part of domestic science

Internet Q & A Forum (Yahoo Chiebukuro) IF

Domain/Field

Languages,Linguistics and

PhilosophyLP

History andEthnology

HE

Literary Works/Imaginative Texts

STScience andTechnology

Biology andMedicine

BM

AH

Politics andLaw

Economics andCommerce

Sociology,Education andOther Social

Issues

PL

EC

SE

Arts and OtherHumanities

Page 24: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

4. Tiers of Japanese vocabulary (3) -1 Academic words (AW)

• JAWL = Japanese Academic Word List• High specificity in 3 or 4 academic domains• 4-domain words (cut off point: LLR > 0)• 3-domain words (cut off point: LLR > 0)

• Level 0 - VIII   9 levels , 2590 words in total • JAWL I (Intermediate): most essential for learning• Basic words contains much fewer academic words• JAWL I: 559 words

Close to AWL in number and text coverageCoverage in the academic corpus used for extracting AWAWL: 10.0 % JAWL I: 11.1 %

Page 25: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Academic Words: Words which are shared by 3 or 4 main academic domains

Ah Ss1 1

22 2

3 3

2 4 2

3 3

Tn Bn

1 2 1

Ah: Arts & Humanities, Ss: Social Sciences,Tn: Technological Natural Sciences, Bn: Biological Natural Sciences

Page 26: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Distribution and examples of JAWL

4 31 科学 規則 割合 生産 産業 講義

science, rule, proportion,ptoduction, industry, lecture

3 39 人口 スクリーン 数学 競争 工業 地理

population, screen, mathmatics,competition, manufacture, geography

JAWL I 4 559 発足 半数 配分 縮小 適正 見直し

inauguration, half the number, allocation,downsize, proper, reconsider

JAWL II 3 542 演説 大小 実情 ステージ ライフ 担保

speech, size, real situation,stage, life, guarantee

JAWL III 4 212 難問 能動 付随 定型 除 本稿

difficult problem, active, accompany,standard, except, this article

JAWL IV 3 452 交錯 カウント 精度 一因 箇年 エンド

mixture, count, accuracy,one cause, -year, end

JAWL V 4 103 併存 親和 盛況 散在 補填 関わり合う

coexistence, affinity, prosperity,straggle, compensation, implicated

JAWL VI 3 328 帰着 編著 沿海 拮抗 常套 内情

come down to, written and edited, coastal,close competition, conventional, internal condition

JAWL VII 4 56 閉 増刊 含意 複 活路 所与

closed, extra edition, implication,double-, way out, given

JAWL VIII 3 269 極小 付則 深度 概算 頒布 円錐

minimal, additional clause, depth,rough estimate, distribution (of goods/paper), cone

Least Frequent 6 Wordsin Each Domain

JAWL 0 L3 679-1288 Basic

Translation of the Least Frequent 6Words in Each Domain

JAWLLabel

FormerJLPTLevel

WordRankings forInternational

Students

Level

Number ofHigh

SpecificityDomains

among the 4ScienceDomains

Numberof UniqueLexemes

L2L1

Other

1289-5000 Inter.

5001-10000 Adv. 1

10001-15000 Adv. 2

15000-20000Super-

adv.

Page 27: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

4. (3) -1 Academic words (AW)Semantic features of AW (1)

• Highly abstract, essential for operating logici.e.

• Range: 占める (occupy, account for), 特殊 (special, particular)• Relation: 属する (belong to), 依存 (rely/reliance)• Comparison/Evaluation: 後者 (the latter), 優れる (superior), • Quantitative change: 減少 (decrease), 強化 (reinforce)• Stage: 当初 (beginning), 現状 (present condition)• Development of enunciation: 取り上げる (take up [an issue]), まとめる (summarize)• Cause-effect, degree, agent, action, object, direction, goal,

instrument, time etc.

Page 28: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

The most frequent Kanji used for AW合 (combine, together), 定 (fix, certain), 分 (divide, minute), 一 (one), 同 (same), 数 (number), 上 (up), 体 (body), 出 (out), 大 (large)

• 3-domain words: Some words have concrete meanings e.g. 署名 (signature), 保健 (health, hygiene)• 4-domain words: Few words have concrete meanings• The nature of the words are the same at all levels

4. Tiers of Japanese vocabulary (3) -1 Academic words (AW)Semantic features of AW (2)

Page 29: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

POS of Japanese AW (1)• Common noun: 1072 words (41.4 %) e.g. 背景 (background)• Verbal noun: 882 words (34.0 %) e.g. 連続 (establish/-ment) Adding other types of nouns together,

    2104 words (81.2 %) can be a noun• Verb (excluding verbal nouns): 225 words (8.7 %) e.g. 認める (recognize/approve) 述べる (describe/mention) Adding other types of verbs together,

1107 words (42.7%) can be a verb• Adjectival noun: 95 words (3.7 %) e.g. 詳細 (detail/-ed), 平等 (equal/-ity)• Adjective : Only 9 words (0.3 %) e.g. 著しい (remarkable)

Page 30: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

POS of Japanese AW (2)• Affix: 106 words (4.1 %) e.g. - 期 (period), - 種 (type)

substantial in Japanese academic words• Adverb: 34 words (1.3 %) e.g. しばしば (frequently)

• Other (particle, auxiliary verb etc.): 22 words (0.8 %)• Remarkably many archaic words  e.g. のみ (only), つつ (while doing), べし (ought to), あらゆる (every)

いかなる (any), 我が (my), 漠然 (vague)

• れる / られる (Passive/Potential/Spontaneous) specific in academic texts

Page 31: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

4. (3) -2 Limited-academic-domain words (LAD)

• Limited-academic-domain words (LAD)• High specificity in 2 or 1 domain(s)• 2-domain words (cut off point: LLR > 1)• 1-domain words (cut off point: LLR > average value)

• Something between “academic” and “technical”• The “scams” from extracting AW?• Tiers of curriculum cf. Tajino et al. (2007)• Words correspondent to the curriculum

• Basic: all the learners• Academic words: prep. to first year• Limited-academic-domain words (?): prep. to major• Technical words: major to postgrad.

Page 32: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Number of Shared Academic Domains among the four academic domainsLimited-Academic-Domain Words:

Words which are shared by only 1 or 2 main academic domain(s)

Ah Ss1 1

22 2

3 3

2 4 2

3 3

1 2 1

Tn Bn

Ah: Arts & Humanities, Ss: Social Sciences,Tn: Technological Natural Sciences, Bn: Biological Natural Sciences

Page 33: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

4. (3) -2 Limited-academic-domain words (LAD)

2 domain wordsDistribution of 2-Domain Words of Japanese Limited-Academic-Domain Words (JLAD)

JLAD 0 L3 679-1288 Basic 15 5 4 5 6 10 45

JLAD I 1289-5000 Inter. 139 27 30 77 57 61 391

JLAD III 5001-10000 Adv. 1 138 38 25 86 50 92 429

JLAD V 10001-15000 Adv. 2 91 28 22 58 37 60 296

JLAD VII 15000-20000Super-adv. 93 23 17 43 16 40 232

476 121 98 269 166 263 1393Ah: Arts & Humanities, Ss: Social Sciences, Tn: Technological Natural Sciences, Bn: Biological Natural Sciences

Total

Total

Numberof UniqueLexemes

in LAD ofTn & Bn

Numberof UniqueLexemes

in LAD ofSs & Tn

Numberof UniqueLexemes

in LAD ofSs & Bn

L2L1

Other

JLADLabel

FormerJLPTLevel

WordRankings forInternational

Students

Level

Numberof UniqueLexemesin LAD ofAh & Ss

Numberof UniqueLexemes

in LAD ofAh & Tn

Numberof UniqueLexemesin LAD ofAh & Bn

Page 34: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

4. (3) -2 Limited-academic-domain words (LAD)

2 domain wordsExamples of 2-Domain Words of Japanese Limited-Academic-Domain Words (JLAD)

JLAD 0 L3 679-1288 Basic 貿易輸出

砂テキスト

発音ステレオ

製レポート

以内パート

アルコール

テニス

JLAD I 1289-5000 Inter. 孤立融資

オールペーパー

静岡書簡

ニーズ顧客

総務性的

スイッチ

JLAD III 5001-10000 Adv. 1 容れる教義

音響流布

発現海域

本件セクション

閉塞弱める

多用部位

JLAD V 10001-15000 Adv. 2 払い戻しユ ニ バ ー シ テ ィ

落差コロン

目付け生長

VTRリハーサル

所見救命

光学ペーハー

JLAD VII 15000-20000Super-adv.

峻別公債

目配りテクノ

太極増量

パレット軽微

マンガン居宅

棒状雨水

LeastFrequent2 Words

in LAD ofTn & Bn

LeastFrequent2 Words

in LAD ofSs & Tn

L2L1

Other

LeastFrequent2 Words

in LAD ofSs & Bn

LeastFrequent2 Words

in LAD ofAh & Ss

LeastFrequent2 Words

in LAD ofAh & Tn

LeastFrequent2 Words

in LAD ofAh & Bn

FormerJLPTLevel

WordRankings forInternational

Students

LevelJLADLabel

Page 35: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

4. (3) -2 Limited-academic-domain words (LAD)

2 domain wordsExamples of 2-Domain Words of Japanese Limited-Academic-Domain Words (Translation)

JLAD 0 L3 679-1288 Basictradeexport

sandtext

pronunciation

stereomade (in)

reportwithin

part(-timer)

alcoholtennis

JLAD I 1289-5000 Inter.isolation

loanall

paperShizuoka pref./city

epistleneed (n.)customer

general affairs

sexualswitchliquid

JLAD III 5001-10000 Adv. 1compatible

doctrineaccousticcirculation

manifestation

watersthis matter

sectionimpasseweaken

frequent useregion (of body)

JLAD V 10001-15000 Adv. 2refund

universitya dropcologne

overseergrowth

VTRrehearsal

remark (n.)lifesaving

opticspH

JLAD VII 15000-20000Super-adv.

sharp distinction

public bond

meticulous care

techno-tai ji

increase in quantity

palletslight

manganesedwelling

stick-shaped

rainwater

Translation ofthe Least

Frequent 2Words in LAD

of Ss & Bn

Translation ofthe Least

Frequent 2Words in LAD

of Tn & Bn

L2L1

Other

WordRankings forInternational

Students

Translation ofthe Least

Frequent 2Words in LAD

of Ah & Ss

JLADLabel

Former JLPTLevel

Level

Translation ofthe Least

Frequent 2Words in LAD

of Ah & Tn

Translation ofthe Least

Frequent 2Words in LAD

of Ah & Bn

Translation ofthe Least

Frequent 2Words in LAD

of Ss & Tn

Page 36: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Examples of 2 domain words: Words which are shared by only 2 main academic domains

Ah Ss

liquidfrequent use

Tn pH Bn

Ah: Arts & Humanities, Ss: Social Sciences,Tn: Technological Natural Sciences, Bn: Biological Natural Sciences

sexualweaken

lifesaving

isolationdoctrinerefund

paperaccoustic a drop

epistlewatersgrowth

need (n.)sectionVTR

Page 37: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

4. (3) -2 Limited-academic-domain words (LAD)

2 domain words• Semantic features

• More concrete and specific than academic words• Ah & Ss: Social, overlap in history and ethnology• Ss & Tn: Industrial• Ss & Bn: Social security, medical and nursing service• Tn & Bn: Scientific

• Ah & Tn, Ah & Bn: not clear

Page 38: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

4. (3) -2 Limited-academic-domain words (LAD)

1 domain words• It is merely a trial• The corpus is not the best for academic purpose, especially for

natural sciences• Extracting something common across domains is much easier

while extracting words by only one target corpus will require more complete target corpus

• Therefore, AW (4 domain words and 3 domain words) will be more reliable than LAD (2 domain words and 1 domain words)

Page 39: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

4. (3) -2 Limited-academic-domain words (LAD)

1 domain wordsDistribution of 1 Domain Words of Japanese Limited-Academic-Domain Words (JLAD)

JLAD 0 L3 679-1288 Basic 13 6 5 9 33

JLAD I 1289-5000 Inter. 104 111 46 52 313

JLAD III 5001-10000 Adv. 1 104 127 60 68 359

JLAD V 10001-15000 Adv. 2 71 74 48 54 247

JLAD VII 15000-20000Super-adv. 60 55 29 53 197

352 373 188 236 1149Ah: Arts & Humanities, Ss: Social Sciences, Tn: Technological Natural Sciences, Bn: Biological Natural Sciences

L2L1

Other

Total

Numberof UniqueLexemes

in Ss

Numberof UniqueLexemes

in Tn

Numberof UniqueLexemes

in Bn

TotalJLADLabel

FormerJLPTLevel

WordRankings forInternational

Students

Level

Numberof UniqueLexemes

in Ah

Page 40: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

4. (3) -2 Limited-academic-domain words (LAD)

1 domain words

• Semantic features are much clearer than 2 domain words

Examples of 1 Domain Words of Japanese Limited-Academic-Domain Words (JLAD)

JLAD 0 L3 679-1288 Basic 辞典文法

工場遊び

海岸汽車

退院柔道

JLAD I 1289-5000 Inter. 色彩滋賀

紛争犯

原子コンクリート

拳杉

JLAD III 5001-10000 Adv. 1 王家呪術

超過欠席

硬化ドラッグ

臓器左足

JLAD V 10001-15000 Adv. 2 報国遍歴

持ち分受諾

PM蒸留

卵子緑茶

JLAD VII 15000-20000Super-adv.

厳寒鼎

卸売り引き当て

プログラミング

バラック居合微小

L2L1

Other

LeastFrequent 2

Words in LADof Bn

LeastFrequent 2

Words in LADof Tn

FormerJLPTLevel

Word Rankingsfor

InternationalStudents

Level

LeastFrequent 2

Words in LADof Ah

LeastFrequent 2

Words in LADof Ss

JLADLabel

Page 41: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

4. (3) -2 Limited-academic-domain words (LAD)1 domain words

• Semantic features are much clearer than 2 domain words

Examples of 1 Domain Words of Japanese Limited-Academic-Domain Words (Translation)

JLAD 0 L3 679-1288 Basicdictionarygrammar

factoryplay(ing)

seashoretrain

leave hospitaljudo

JLAD I 1289-5000 Inter.coloring

Shiga (pref.)conflictoffense

atomconcrete (n.)

fist/martial artcedar

JLAD III 5001-10000 Adv. 1royal familyincantation

excessabsence

harden(ing)drag/drug

organleft leg/foot

JLAD V 10001-15000 Adv. 2patrioticitinerancy

quotaacceptance

PMdistillation

ovumgreen tea

JLAD VII 15000-20000Super-adv.

intense coldthree-legged vessel

wholesaleresearve fund

programmingshanty

iai (martial arts)micro

Translation of theLeast Frequent 2

Words in LAD of Bn

L2L1

Other

LevelTranslation of theLeast Frequent 2

Words in LAD of Ah

Translation of theLeast Frequent 2

Words in LAD of Ss

Translation of theLeast Frequent 2

Words in LAD of Tn

JLADLabel

Former JLPTLevel

WordRankings forInternational

Students

Page 42: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Examples of Academic Domain Words:Words which are shared by only 2 main academic domains Words which are shared by 1, 2, 3 or 4 main academic domain(s)

coloring Ssroyal family conflict

Ah excessisolation

epistle doctrine need (n.)waters refund sectiongrowth VTR

guarantee- year

paper sexualaccoustic weaken

a drop lifesavinglead endsize life

Tn liquid Bnfrequent use

atom pH fist/ martial artharden(ing) organ

Ah: Arts & Humanities, Ss: Social Sciences,Tn: Technological Natural Sciences, Bn: Biological Natural Sciences

at a strokemixture

allocation

properexcept

Page 43: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

POS of Japanese LAD (1)• Common noun: 1605 words (63.1 %) – more than AW (41.4%)• Verbal noun: 633 words (24.9 %) e.g. 融資 (finance) cf. AW

(34.0%) Adding other types of nouns together,

    2104 words (87.9 %) can be a noun – more than AW (81.2%)• Verb (excl. verbal nouns): 81 words (3.2 %) cf. AW (8.7%) e.g. 訳す (translate) 向き合う (face (v.)) Adding other types of verbs together,

714 words (28.1%) can be a verb – less than AW (42.7%)• Adjectival noun: 88 words (3.5 %) cf. AW (3.7%) e.g. フル (full), 偉大 (great)• Adjective : Only 3 words (0.1 %) cf. AW (0.3%) e.g. 硬い (stiff)

Page 44: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

POS of Japanese LAD (2)• Affix: 109 words (4.3%) cf. AW (4.1%) e.g. –犯 (offense)

substantial in Japanese academic domain words• Adverb: 15 words (0.6 %) cf. AW (1.3%) e.g. 現に (surely)

• Other (particle, auxiliary verb etc.): 9 words (0.8 %)cf. AW (0.8%)

• Remarkably many archaic words   – similar to AW  e.g. なり [affirmative aux.], とも (even though), たり [affirmative aux.], ごとし (as/like), 単なる

(mere), しめる(=しむ) [causative aux.], かかる (such)

Page 45: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

4. Tiers of Japanese vocabulary (4) Literary words (LW)Extracting literary words: Words for reading literary works• Log-likelihood ratio (Keyness in AntConc)• Target corpus: literary works (identified by NDC and C-code) in

BCCWJ 2009 (NINJAL, 2009) – Over 8 million tokens• 4 different reference corpus: Technical texts, general texts in arts

and humanities, general texts in the other 3 academic domains, Internet forum texts (Yahoo Chiebukuro)

• Extract keywords shared by the four results (Cutoff point: average value)• Eliminate the former JLPT Level 4 vocabulary (Top 700 words)• Eliminate the words ranked at 20001 or lower• Classify all the LW by word ranking levels for International Students

(U=Usage Coefficient)

Page 46: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

4. (4) Literary words (LW) Distribution and examples

Distribution and examples of Japanese Literay Words (JLW)

L3 679-1288 Basic Lit. 142 ちっとも引き出し

(not) at alldrawer

1289-5000 Inter. Lit 446 戸惑う吐き出す

puzzledvent

5001-10000 Adv. 1 Lit. 483 不吉銀色

ominoussilver

10001-15000 Adv. 2 Lit. 345 敵機口笛

hostile aircraftwhistle

15000-20000Super-adv.

Lit. 200 香菜樹海

coriandersea of trees

Total 1616

L2L1

Other

Least Frequent 2Words of JLW

FormerJLPTLevel

WordRankings forInternational

Students

JLW Label

Number ofUnique

Lexemes ofJLW

Translation of theLeast Frequent 2

Words of JLW

Page 47: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

4. (4) Literary words (LW) POS of LW

• More verbs, adverbs and interjections than AW and LAD

• Less verbal nouns and adjectival nouns

• This inevitably means LW have less loan words but more Japanese-origin words.

Number of Unique Lexemes of Japanese Literary Words by POS

56 9 49 2 1 3 10 12 142

168 21 157 20 12 8 28 32 446

199 23 163 25 13 12 28 20 483

137 19 122 15 7 2 27 16 345

85 14 58 5 8 1 21 8 200

645 86 549 67 41 26 114 88 1616

N.(Excl.VN. &AN,)

VN AffixAdj.AN.

(Excl.VN.)

VN: Verbal Noun AN: Adjectival Noun

V.(Excl.VN.)

Adv. TotalOthers

Page 48: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

4. (4) Literary words (LW)Q. How many LW overlap with AW and LAD?• Only 27 words (0.5% of academic domain words, 1.7% of LW) are

overlapping• Most of the overlapping words (24/27) overlap with 1 domain words

(17 words overlap with words in biological natural science) • Many physical words such as words for body parts e.g. 左手 (left hand), こぶし (fist), 血 (blood),頭上 (overhead)• No LW words overlap with 4 domain words• Overlapping words are mainly at the intermediate level• No overlapping words in or above 11K+• Some examples of overlapping words: 音 (sound), 光 (light), 棚 (shelf), 組 (class), 岩 (rock), ひざ (knee), 興奮 (excite/-ment), 全身 (whole body), 帝 (emperer), ネズミ (mouse), 帆 (sail)

Page 49: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Word tiers: In what order should students learn them?

• Basic• General• AW/LAD• LW

• Intermediate• General• AW/LAD• LW

• Advanced• General• AW/LAD• LW

• Highly Advanced• General• AW/LAD• LW

• Super-Advanced• General• AW/LAD• LW

• Assumed known words• Proper names• Fillers, Signs• (Transparent compounds *)

• Others

Page 50: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

5. Text coverage by word tier• The word tier analyser: An Excel sheet where word

profiling of a text can be checked automatically by cutting and pasting the result of AntWordProfiler with the word tier base word list.

• Text covering efficiency High efficiency in vocabulary learning = Fewer unique lexemes cover more texts (Reciprocal Type/Token Ratio = Token/Type Ratio?) *Comparison should be made between equally-sized texts)

Page 51: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Coverage of Japanese texts by word tierMC UPC OB BCCWJ WP UYN TIS TB MTC- Ss MTC- Tn MTC-Bn

Conversation

Non-academic

prose

Bestsellerbooks

(dominantly novels)

Books &InternetForum

Wikipedia Newspaper

Humanities &

SocialSciences

SocialSciences

SocialSciences

Technological

NaturalSciences

BiologicalNatural

Sciences

1.13 2.10 2.30 32.82 5.90 5.68 0.04 0.19 0.05 0.07 0.01

Word Tier (*)

Total # ofTypes inEach Tier(Lexeme)

AKW (**) (Proper nouns etc.) (30821) 1.7 1.3 2.4 2.0 3.7 1.3 0.9 0.4 0.3 0.6 0.3General 13303 81.0 77.2 78.0 74.7 64.9 63.5 66.1 66.0 67.2 61.1 61.6Academic 2590 2.7 7.6 7.2 10.9 14.9 20.7 20.7 21.3 20.9 23.2 22.7Limited-Aca.-Dom. 2542 1.6 3.2 3.8 5.3 7.3 11.2 8.9 8.9 7.7 5.9 6.8Literary 1616 10.8 7.4 6.5 4.6 1.8 1.7 2.0 1.6 1.6 2.3 1.4Overlap - 27 0.0 - 0.2 - 0.2 - 0.1 - 0.1 - 0.1 0.0 0.0 0.0 - 0.1 - 0.121K + Others - - 2.2 3.5 2.2 2.6 7.4 1.7 1.4 1.8 2.4 7.0 7.3

Total 20024 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

% of Tokens (Overlap included)

Total Number of Tokens forEach Test Corpus (Million)

Text Genre

Name of Text

* All words except 'AKW' and '21K+Others' are listed in top 20000 (01K-20K) ranked by the Word List for International Students (Matsushita, 2011)

** AKW (Assumed Known Words): Words such as proper nouns or fillers which are assumed not to require previous learning.

Page 52: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Findings from the text coverage • Conversation and Non-academic texts: more general words and

LW• Wikipedia: more proper nouns and low frequency words• Academic items of Wikipedia: 15-20% of the texts of are

estimated to be covered by JAWL 1 (559 types) – encyclopaedic nature of AW? can be a good resource for learning AW

• Newspapers: similar to academic texts, but contains more LAD and AW at the advanced level

can be a good resource for learning AW (esp. in social sci.)• Academic texts: more AW and LAD but less LW in any academic

domain• Academic texts in natural sciences: more academic domain words

at lower frequency levels (technical vocabulary) than Ah. and Ss. texts – similar to Coxhead, Stevens, & Tinkle (2010)

Page 53: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

6. Proportion of word origin types by word tier

Proportion of Unique Lexemes by Word Origin and Word Tier in 01K-20K (*) (Matsushita, 2011)

Word Origin

Word TierJ apanese

(%)Chinese

(%)

Western &Other(%)

Mixed(%)

ProperNouns

(%)

Unknown& Signs

(%) Total

General 38.4 45.3 10.8 3.2 1.5 0.8 100.0

Academic 15.0 75.2 7.0 1.9 0.4 0.5 100.0

Limited-academic-domain 12.4 69.1 13.7 1.7 2.2 1.0 100.0

Literary 71.7 21.8 2.5 3.1 0.3 0.6 100.0

Overlap 74.1 22.2 0.0 3.7 0.0 0.0 100.0

Total 34.7 50.3 10.0 2.8 1.4 0.8 100.0

*Including 24 compound numerals (01K+)

Page 54: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Findings from the proportion of word origin types by word tier• LW: Japanese origin words are significantly dominant• AW and LAD: Chinese origin words are significantly

dominant• LAD: more Western origin words (Gairaigo) Western origin words tend to appear more at lower

frequency levels in academic domain words• Origins of academic and literary words are

considerably clearly separated: • Academic – Chinese origin• Literary – Japanese origin

Page 55: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

7. Implications from the findingsQ. Word Tiers: In what order should students learn them?

• Basic• Academic• LAD• General

• Intermediate• Academic• LAD• General

• Advanced• Academic• LAD• General

• Highly Advanced• Academic• LAD• General

• Super-Advanced• Academic• LAD• General

• Assumed known words• Proper names• Fillers• Signs• (Transparent compounds *)

• Others

Page 56: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Implications for teaching and research• A vocabulary conscious curriculum should be designed

and incorporated in Japanese programs depending on the learners’ needs and language backgrounds

• The gap between Chinese-background learners (CBLs) and non-CBLs will be less in basic conversation and reading literary works than in reading academic texts

• Good curriculum for learning academic domain words is particularly desired for non-CBLs of academic Japanese

• Autonomous mode for learning vocabulary will be necessary particularly when the learners’ needs and language backgrounds are various

Page 57: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

8. Conclusion

Limitations of the word lists• Less valid in narrower domain words (2D/1D words) and less

reliable in higher frequency levels Need refining by more complete academic corpus

• Multi-word units not extracted• Not sensitive to different usages in different domains (polysemy)

Remaining issues• Many transparent compounds in JapaneseWhat is Kanji tier? How is it related to word tier?

Page 58: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Download sites for VDRJ/JAWLMatsushita Laboratory for Language Learninghttp://www.wa.commufa.jp/~tatsum/English%20top_Tatsu.html(Interface: English)Google it with “matsushita” and “language”

松下言語学習ラボhttp://www.wa.commufa.jp/~tatsum/index.html(Interface: Japanese)Google it with “松下” and “言語”

Page 59: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

Main findings• VDRJ is useful for designing curriculum (material, tests etc.)• The more domains a words is shared as AW or LAD by, the more abstract

the meaning of the word is. • Conversation and non-academic texts contain more general words and

LW• Academic texts: more AW and LAD but less LW in any academic domain• Wikipedia: more proper nouns and low frequency words• Newspapers and academic items of Wikipedia can be a good resource

for learning AW and LAD.• Natural science texts contain more academic domain words at lower

frequency levels than arts and social science texts • Origins of academic and literary words are considerably clearly

separated; 3/4 of LW originate in Japanese while 3/4 of AW and LAD originate in Chinese

• LAD contains more Western origin words (Gairaigo)

Page 60: Tatsuhiko Matsushita LALS, Victoria University of Wellington tatsuhiko.matsushita@vuw.ac.nz

References (1)• Anthony, L. (2007). AntConc Version 3.2.1 (text analysis tool)

http://www.antlab.sci.waseda.ac.jp/software.html (Version 1.0 first published in 2002)

• Anthony, L. (2009). AntWordProfiler Version 1.2 w (word profiler) http://www.antlab.sci.waseda.ac.jp/software.html (Version 1.0 first published in 2008)

• Beck, I. L., McKeown, M. G., & Kucan, L. (2002). Bringing Words to Life: Robust Vocabulary Instruction. Solving problems in the teaching of literacy. New York: Guilford Press.

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