Word lists and history

A word list (or lexicon) is a list of a language’s lexicon (generally sorted by frequency of occurrence either by levels or as a ranked list) within some given text corpus, serving the purpose of vocabulary acquisition. A lexicon sorted by frequency «provides a rational basis for making sure that learners get the best return for their vocabulary learning effort» (Nation 1997), but is mainly intended for course writers, not directly for learners. Frequency lists are also made for lexicographical purposes, serving as a sort of checklist to ensure that common words are not left out. Some major pitfalls are the corpus content, the corpus register, and the definition of «word». While word counting is a thousand years old, with still gigantic analysis done by hand in the mid-20th century, natural language electronic processing of large corpora such as movie subtitles (SUBTLEX megastudy) has accelerated the research field.

In computational linguistics, a frequency list is a sorted list of words (word types) together with their frequency, where frequency here usually means the number of occurrences in a given corpus, from which the rank can be derived as the position in the list.

Type	Occurrences	Rank
the	3,789,654	1st
he	2,098,762	2nd
[…]
king	57,897	1,356th
boy	56,975	1,357th
[…]
stringyfy	5	34,589th
[…]
transducionalify	1	123,567th

MethodologyEdit

FactorsEdit

Nation (Nation 1997) noted the incredible help provided by computing capabilities, making corpus analysis much easier. He cited several key issues which influence the construction of frequency lists:

• corpus representativeness
• word frequency and range
• treatment of word families
• treatment of idioms and fixed expressions
• range of information
• various other criteria

CorporaEdit

Traditional written corpusEdit

Most of currently available studies are based on written text corpus, more easily available and easy to process.

SUBTLEX movementEdit

However, New et al. 2007 proposed to tap into the large number of subtitles available online to analyse large numbers of speeches. Brysbaert & New 2009 made a long critical evaluation of this traditional textual analysis approach, and support a move toward speech analysis and analysis of film subtitles available online. This has recently been followed by a handful of follow-up studies,^[1] providing valuable frequency count analysis for various languages. Indeed, the SUBTLEX movement completed in five years full studies for French (New et al. 2007), American English (Brysbaert & New 2009; Brysbaert, New & Keuleers 2012), Dutch (Keuleers & New 2010), Chinese (Cai & Brysbaert 2010), Spanish (Cuetos et al. 2011), Greek (Dimitropoulou et al. 2010), Vietnamese (Pham, Bolger & Baayen 2011), Brazil Portuguese (Tang 2012) and Portugal Portuguese (Soares et al. 2015), Albanian (Avdyli & Cuetos 2013), Polish (Mandera et al. 2014) and Catalan (2019^[2]). SUBTLEX-IT (2015) provides raw data only.^[1]

Lexical unitEdit

In any case, the basic «word» unit should be defined. For Latin scripts, words are usually one or several characters separated either by spaces or punctuation. But exceptions can arise, such as English «can’t», French «aujourd’hui», or idioms. It may also be preferable to group words of a word family under the representation of its base word. Thus, possible, impossible, possibility are words of the same word family, represented by the base word *possib*. For statistical purpose, all these words are summed up under the base word form *possib*, allowing the ranking of a concept and form occurrence. Moreover, other languages may present specific difficulties. Such is the case of Chinese, which does not use spaces between words, and where a specified chain of several characters can be interpreted as either a phrase of unique-character words, or as a multi-character word.

StatisticsEdit

It seems that Zipf’s law holds for frequency lists drawn from longer texts of any natural language. Frequency lists are a useful tool when building an electronic dictionary, which is a prerequisite for a wide range of applications in computational linguistics.

German linguists define the Häufigkeitsklasse (frequency class)   of an item in the list using the base 2 logarithm of the ratio between its frequency and the frequency of the most frequent item. The most common item belongs to frequency class 0 (zero) and any item that is approximately half as frequent belongs in class 1. In the example list above, the misspelled word outragious has a ratio of 76/3789654 and belongs in class 16.

 

where   is the floor function.

Frequency lists, together with semantic networks, are used to identify the least common, specialized terms to be replaced by their hypernyms in a process of semantic compression.

PedagogyEdit

Those lists are not intended to be given directly to students, but rather to serve as a guideline for teachers and textbook authors (Nation 1997). Paul Nation’s modern language teaching summary encourages first to «move from high frequency vocabulary and special purposes [thematic] vocabulary to low frequency vocabulary, then to teach learners strategies to sustain autonomous vocabulary expansion» (Nation 2006).

Effects of words frequencyEdit

Word frequency is known to have various effects (Brysbaert et al. 2011; Rudell 1993). Memorization is positively affected by higher word frequency, likely because the learner is subject to more exposures (Laufer 1997). Lexical access is positively influenced by high word frequency, a phenomenon called word frequency effect (Segui et al.). The effect of word frequency is related to the effect of age-of-acquisition, the age at which the word was learned.

LanguagesEdit

Below is a review of available resources.

EnglishEdit

Word counting dates back to Hellenistic time. Thorndike & Lorge, assisted by their colleagues, counted 18,000,000 running words to provide the first large-scale frequency list in 1944, before modern computers made such projects far easier (Nation 1997).

Traditional listsEdit

These all suffer from their age. In particular, words relating to technology, such as «blog,» which, in 2014, was #7665 in frequency^[3] in the Corpus of Contemporary American English,^[4] was first attested to in 1999,^[5][6][7] and does not appear in any of these three lists.

The Teachers Word Book of 30,000 words (Thorndike and Lorge, 1944)

The TWB contains 30,000 lemmas or ~13,000 word families (Goulden, Nation and Read, 1990). A corpus of 18 million written words was hand analysed. The size of its source corpus increased its usefulness, but its age, and language changes, have reduced its applicability (Nation 1997).

The General Service List (West, 1953)

The GSL contains 2,000 headwords divided into two sets of 1,000 words. A corpus of 5 million written words was analyzed in the 1940s. The rate of occurrence (%) for different meanings, and parts of speech, of the headword are provided. Various criteria, other than frequence and range, were carefully applied to the corpus. Thus, despite its age, some errors, and its corpus being entirely written text, it is still an excellent database of word frequency, frequency of meanings, and reduction of noise (Nation 1997). This list was updated in 2013 by Dr. Charles Browne, Dr. Brent Culligan and Joseph Phillips as the New General Service List.

The American Heritage Word Frequency Book (Carroll, Davies and Richman, 1971)

A corpus of 5 million running words, from written texts used in United States schools (various grades, various subject areas). Its value is in its focus on school teaching materials, and its tagging of words by the frequency of each word, in each of the school grade, and in each of the subject areas (Nation 1997).

The Brown (Francis and Kucera, 1982) LOB and related corpora

These now contain 1 million words from a written corpus representing different dialects of English. These sources are used to produce frequency lists (Nation 1997).

FrenchEdit

Traditional datasets

A review has been made by New & Pallier.
An attempt was made in the 1950s–60s with the Français fondamental. It includes the F.F.1 list with 1,500 high-frequency words, completed by a later F.F.2 list with 1,700 mid-frequency words, and the most used syntax rules.^[8] It is claimed that 70 grammatical words constitute 50% of the communicatives sentence,^[9] while 3,680 words make about 95~98% of coverage.^[10] A list of 3,000 frequent words is available.^[11]

The French Ministry of the Education also provide a ranked list of the 1,500 most frequent word families, provided by the lexicologue Étienne Brunet.^[12] Jean Baudot made a study on the model of the American Brown study, entitled «Fréquences d’utilisation des mots en français écrit contemporain».^[13]

More recently, the project Lexique3 provides 142,000 French words, with orthography, phonetic, syllabation, part of speech, gender, number of occurrence in the source corpus, frequency rank, associated lexemes, etc., available under an open license CC-by-sa-4.0.^[14]

Subtlex

This Lexique3 is a continuous study from which originate the Subtlex movement cited above. New et al. 2007 made a completely new counting based on online film subtitles.

SpanishEdit

There have been several studies of Spanish word frequency (Cuetos et al. 2011).^[15]

ChineseEdit

Chinese corpora have long been studied from the perspective of frequency lists. The historical way to learn Chinese vocabulary is based on characters frequency (Allanic 2003). American sinologist John DeFrancis mentioned its importance for Chinese as a foreign language learning and teaching in Why Johnny Can’t Read Chinese (DeFrancis 1966). As a frequency toolkit, Da (Da 1998) and the Taiwanese Ministry of Education (TME 1997) provided large databases with frequency ranks for characters and words. The HSK list of 8,848 high and medium frequency words in the People’s Republic of China, and the Republic of China (Taiwan)’s TOP list of about 8,600 common traditional Chinese words are two other lists displaying common Chinese words and characters. Following the SUBTLEX movement, Cai & Brysbaert 2010 recently made a rich study of Chinese word and character frequencies.

OtherEdit

Most frequently used words in different languages based on Wikipedia or combined corpora.^[16]

See alsoEdit

• Letter frequency
• Most common words in English
• Long tail
• Google Ngram Viewer – shows changes in word/phrase frequency (and relative frequency) over time

NotesEdit

ReferencesEdit

Theoretical conceptsEdit

• Nation, P. (1997), «Vocabulary size, text coverage, and word lists», in Schmitt; McCarthy (eds.), Vocabulary: Description, Acquisition and Pedagogy, Cambridge: Cambridge University Press, pp. 6–19, ISBN 978-0-521-58551-4
• Laufer, B. (1997), «What’s in a word that makes it hard or easy? Some intralexical factors that affect the learning of words.», Vocabulary: Description, Acquisition and Pedagogy, Cambridge: Cambridge University Press, pp. 140–155, ISBN 9780521585514
• Nation, P. (2006), «Language Education — Vocabulary», Encyclopedia of Language & Linguistics, Oxford: 494–499, doi:10.1016/B0-08-044854-2/00678-7, ISBN 9780080448541.
• Brysbaert, Marc; Buchmeier, Matthias; Conrad, Markus; Jacobs, Arthur M.; Bölte, Jens; Böhl, Andrea (2011). «The word frequency effect: a review of recent developments and implications for the choice of frequency estimates in German». Experimental Psychology. 58 (5): 412–424. doi:10.1027/1618-3169/a000123. PMID 21768069. database
• Rudell, A.P. (1993), «Frequency of word usage and perceived word difficulty : Ratings of Kucera and Francis words», Most, vol. 25, pp. 455–463
• Segui, J.; Mehler, Jacques; Frauenfelder, Uli; Morton, John (1982), «The word frequency effect and lexical access», Neuropsychologia, 20 (6): 615–627, doi:10.1016/0028-3932(82)90061-6, PMID 7162585, S2CID 39694258
• Meier, Helmut (1967), Deutsche Sprachstatistik, Hildesheim: Olms (frequency list of German words)
• DeFrancis, John (1966), Why Johnny can’t read Chinese (PDF)
• Allanic, Bernard (2003), The corpus of characters and their pedagogical aspect in ancient and contemporary China (fr: Les corpus de caractères et leur dimension pédagogique dans la Chine ancienne et contemporaine) (These de doctorat), Paris: INALCO

Written texts-based databasesEdit

• Da, Jun (1998), Jun Da: Chinese text computing, retrieved 2010-08-21.
• Taiwan Ministry of Education (1997), 八十六年常用語詞調查報告書, retrieved 2010-08-21.
• New, Boris; Pallier, Christophe, Manuel de Lexique 3 (in French) (3.01 ed.).
• Gimenes, Manuel; New, Boris (2016), «Worldlex: Twitter and blog word frequencies for 66 languages», Behavior Research Methods, 48 (3): 963–972, doi:10.3758/s13428-015-0621-0, ISSN 1554-3528, PMID 26170053.

SUBTLEX movementEdit

• New, B.; Brysbaert, M.; Veronis, J.; Pallier, C. (2007). «SUBTLEX-FR: The use of film subtitles to estimate word frequencies» (PDF). Applied Psycholinguistics. 28 (4): 661. doi:10.1017/s014271640707035x. hdl:1854/LU-599589. S2CID 145366468. Archived from the original (PDF) on 2016-10-24.
• Brysbaert, Marc; New, Boris (2009), «Moving beyond Kucera and Francis: a critical evaluation of current word frequency norms and the introduction of a new and improved word frequency measure for American English» (PDF), Behavior Research Methods, 41 (4): 977–990, doi:10.3758/brm.41.4.977, PMID 19897807, S2CID 4792474
• Keuleers, E, M, B.; New, B. (2010), «SUBTLEX—NL: A new measure for Dutch word frequency based on film subtitles», Behavior Research Methods, 42 (3): 643–650, doi:10.3758/brm.42.3.643, PMID 20805586
• Cai, Q.; Brysbaert, M. (2010), «SUBTLEX-CH: Chinese Word and Character Frequencies Based on Film Subtitles», PLOS ONE, 5 (6): 8, Bibcode:2010PLoSO…510729C, doi:10.1371/journal.pone.0010729, PMC 2880003, PMID 20532192
• Cuetos, F.; Glez-nosti, Maria; Barbón, Analía; Brysbaert, Marc (2011), «SUBTLEX-ESP : Spanish word frequencies based on film subtitles» (PDF), Psicológica, 32: 133–143
• Dimitropoulou, M.; Duñabeitia, Jon Andoni; Avilés, Alberto; Corral, José; Carreiras, Manuel (2010), «SUBTLEX-GR: Subtitle-Based Word Frequencies as the Best Estimate of Reading Behavior: The Case of Greek», Frontiers in Psychology, 1 (December): 12, doi:10.3389/fpsyg.2010.00218, PMC 3153823, PMID 21833273
• Pham, H.; Bolger, P.; Baayen, R.H. (2011), «SUBTLEX-VIE : A Measure for Vietnamese Word and Character Frequencies on Film Subtitles», ACOL
• Brysbaert, M.; New, Boris; Keuleers, E. (2012), «SUBTLEX-US : Adding Part of Speech Information to the SUBTLEXus Word Frequencies» (PDF), Behavior Research Methods: 1–22 (databases)
• Mandera, P.; Keuleers, E.; Wodniecka, Z.; Brysbaert, M. (2014). «Subtlex-pl: subtitle-based word frequency estimates for Polish» (PDF). Behav Res Methods. 47 (2): 471–483. doi:10.3758/s13428-014-0489-4. PMID 24942246. S2CID 2334688.
• Tang, K. (2012), «A 61 million word corpus of Brazilian Portuguese film subtitles as a resource for linguistic research», UCL Work Pap Linguist (24): 208–214
• Avdyli, Rrezarta; Cuetos, Fernando (June 2013), «SUBTLEX- AL: Albanian word frequencies based on film subtitles», ILIRIA International Review, 3 (1): 285–292, doi:10.21113/iir.v3i1.112, ISSN 2365-8592
• Soares, Ana Paula; Machado, João; Costa, Ana; Iriarte, Álvaro; Simões, Alberto; de Almeida, José João; Comesaña, Montserrat; Perea, Manuel (April 2015), «On the advantages of word frequency and contextual diversity measures extracted from subtitles: The case of Portuguese», The Quarterly Journal of Experimental Psychology, 68 (4): 680–696, doi:10.1080/17470218.2014.964271, PMID 25263599, S2CID 5376519

History, like many disciplines, has its own distinctive styles of writing. While learning to think about the past, history students must also learn to write history in a clear and convincing manner. Those who are already strong writers will relish this challenge but others may find it confronting.

This page contains several lists of ‘history words’ to provide you with a head start in writing history. You will encounter many of these words when reading history while others are useful descriptive words you can use in your own writing. These lists are not comprehensive or exhaustive but may prove useful for inexperienced writers.

If you are new to history, or have difficulty finding the right words, save or print off these lists and keep them to hand. If you would like to suggest words for these lists, please make contact with your ideas.

Sections or groups in society

academia	People who work in schools and universities, teaching or undertaking research
agrarian	People involved in producing crops and livestock through farming
aristocracy	People who possess noble titles and privileges, often with wealth and power
artisans	People involved in the manufacture or repair of items, such as mechanics
bourgeoisie	People who own capital, such as land, factories and raw materials
capitalist	As for bourgeoisie (above), people who own capital and the means of production
clergy	People ordained by the church to carry out its functions, such as priests, monks and nuns
commercial	People involved in trade, such as importing and exporting, buying and selling
economic	People, institutions and activities that produce society’s wants and needs
establishment	The political, social and economic elites who wield power in a society
gender	Refers to the rights, roles and conditions of men and women in a society
industrial	The mass production of wants and needs, particularly on a large scale
intelligentsia	People who develop ideas, theories and policies in a society
middle class	The social classes who own some property and enjoy safe and stable standards of living
military	A state’s defence forces, such as the army, navy and air force
monarchy	The institution of hereditary royalty, led by a king, queen or emperor
nobility	People who possess noble titles, either from birth, royal grant or venality
peasantry	People who work the land, usually as tenant farmers and often in impoverished conditions
philosophes	Intellectuals and writers who engage in critical study of society, beliefs and ideas
political	The people, bodies and processes that govern and make decisions in a society
proletariat	People who work for wages in a society, particularly in the industrial sector
provincial	The areas of a nation outside major cities, such as lesser towns, rural areas or colonies
upper class	The upper levels of a society, such as royalty, aristocracy and the very wealthy
urban	The people, actions and conditions in large cities
village	A small agricultural community, usually in a rural area
working class	The lower levels of society, whose members must work to survive

Political systems

absolutism	Any political system where the ruler or government wields absolute power
anarchism	A political system that seeks to abolish the state and create a communal society
autocracy	A system where political power is concentrated in the hands of a single person
capitalism	An economic system where most companies, land and other resources are privately owned
colonialism	A system of claiming, settling, ruling and maintaining one or more colonies (see imperialism)
communism	A political-economic system with no state, minimal class differences and economic equality
constitutional monarchy	A political system with a monarch whose power is limited and shared with the people
democracy	A political system where the government or parts of it are selected by the people
divine right	A form of political authority where power is said to be ordained by God
fascism	A political system marked by authoritarian rule, nationalism, state and military power
feudalism	A medieval socio-political system with a hierarchy of kings, lords, knights and vassals
imperialism	A system where a powerful state conquers territories (colonies) for its own gain
Marxism	A system or world view based on material factors, inequalities of wealth and class struggle
mercantilism	An economic system designed to increase national power by increasing wealth and trade
militarism	A system where military needs are prioritised and the military exerts political influence
nationalism	An ideology urging loyalty to one’s own country; to put your country first
popular sovereignty	A form of political authority where power is derived from the consent of the people
socialism	A system where the government rules in the interests of the workers or common people
syndicalism	A form of socialism where the workers collectively control their factories or workplaces
theocracy	A system where government and laws are determined by religious leaders and teachings
totalitarianism	A political system where the power of the state often overrides the rights of individuals
welfare state	A system that provides necessities of life to the homeless, unemployed, sick or elderly

Political concepts

assembly	A body of people, elected or appointed to form government or make decisions
autocracy	A form of government where one person is responsible for decision making
constitution	A document defining systems of government and the limits of government power
democracy	A political system where government is formed by popular elections
divine right	The idea that governments and autocrats derive their power and authority from God
elections	The process of voting to select others, usually to form a representative government
executive	The branch of government responsible for leadership and day to day decision making
government	A system responsible for leadership, making decisions and making laws in a society
ideology	A system of ideas and beliefs that shapes one’s views about politics and government
legislature	An assembly that exists to pass new laws or review, amend or abolish existing laws
parliament	An elected legislature from which an executive government is also formed
participation	The involvement of ordinary people in selecting government and in political discourse
popular sovereignty	The idea that governments derive their power and authority from the consent of the people
representation	A political concept where some individuals act, speak or make decisions on behalf of others
sovereignty	The supreme authority of a government, the basis for its power and autonomy
state	‘The state’ describes an organised society and the political system that governs it

Economic concepts

capital	The resources needed to produce things, such as land, raw materials and equipment
commerce	The business of buying and selling, particularly on a large scale
debt	Money owed to another party, usually because it has been previously borrowed
deficit	The shortfall that exists when spending is greater than income
exports	Resources or goods sold and shipped to another country, which boosts national income
finance	Describes the sections of an economy concerned with managing money, such as banking
imports	Resources or goods bought and shipped in from another country, depleting national income
industry	The production of raw materials and manufactured goods within an economy
inflation	An increase in prices for goods and services, reducing the purchasing power of money
labour	The people who provide work to enable production or delivery of services; the workers
laissez-faire	French for “let it be”; an economy free of trade regulations, tariffs or costs
manufacturing	The process of making or producing goods, particularly on a large scale
production	The process of making things, particularly things that have additional value
profit	Financial reward obtained from business or investment, where income exceeds costs
revenue	Money received for normal activities, such as sales (business) or taxation (government)
taxation	Money collected from individuals and groups by the government to fund the state
trade	The buying or selling of goods, usually in exchange for money

Words for describing historical cause

agitated	aroused	awakened	brought about	catalyst
developed	deteriorated	encouraged	exacerbated	fuelled
generated	incited	inflamed	instigated	kindled
led to	long term	motivated	popularised	propagandised
prompted	promoted	protested	provoked	radicalised
reformed	rocked	roused	set off	short term
solicited	sparked	spurred	stimulated	stirred up
transformed	triggered	urged	whipped up	worsened

Words for describing historical effect or consequence

boosted	catastrophic	consolidated	crippled	decimated
demoralised	depleted	disastrous	disbanded	disoriented
dispersed	dissolved	divided	drained	elevated
emboldened	enriched	exhausted	fatigued	hardened
heartened	improved	inspired	mobilised	prospered
punished	restored	sapped	scattered	separated
stimulated	strained	strengthened	stretched	unified
united	unsettled	uplifted	upset	wearied

Words for describing historical continuity

blocked	calmed	censored	clamped down	concealed
conservative	contained	curbed	deterred	dispersed
froze	halted	held back	limited	mollified
pacified	oppressed	overpowered	prohibited	quashed
quelled	reactionary	regressed	repressed	resisted
restored	restrained	restricted	smothered	stabilised
stemmed	stunted	subdued	suppressed	wound back

Words for describing historical significance

adverse	calamitous	catastrophic	destabilising	destructive
devastating	dire	disastrous	essential	expedient
far reaching	far sighted	fateful	forerunner	ground breaking
healing	important	innovative	meaningful	modernising
negative	ominous	opportune	profound	pivotal
positive	revolutionary	ruinous	serious	shaking
shattering	significant	spear heading	timely	trail blazing
transforming	tumultuous	unsettling	uprooting	vital

Words for evaluating historical sources

balanced	baseless	biased	convincing	credible
deceptive	dishonest	distorted	doubtful	dubious
emotive	exaggerated	fallacious	far fetched	flawed
honest	imbalanced	impossible	inflated	limited
misleading	one sided	overwrought	persuasive	phoney
plausible	propagandist	realistic	reasonable	selective
sensationalist	skewed	sound	spurious	unrealistic
unreliable	untenable	useful	valid	vivid

Command words for history tasks and activities

analyse	Examine and discuss the important structure or parts of something
annotate	Record written questions, comments or explanations on a document or visual source
annotated bibliography	A list of books that contains a note about the content and usefulness of each book
argue	Present a case, to express and explain a particular reason or theory
brainstorm	Gather and record thoughts and ideas spontaneously, without sorting or evaluating them
cite	Refer to an authority or trusted source, as evidence of your information or idea
compare	Examine two or more propositions and identify and discuss similarities between them
concept map	A visual chart or diagram, using shapes and lines to organise and connect topics or ideas
conclusion	The last paragraph in sustained writing, it restates the contention and ’rounds off’ the text
contrast	Examine two or more propositions and identify and discuss differences between them
critically analyse	Analyse something and offer views and judgements about the merit or value of its parts
define	Provide precise meanings and explanations about something
describe	Provide a detailed and graphic account of something
discuss	Provide a balanced commentary about something, mentioning arguments for and against
evaluate	Analyse something and form final conclusions about its value, credibility or merit
explain	Provide a clear, straightforward and detailed account of something
historiographical activity	A task requiring discussion of historians and their interpretations of a particular topic
interpret	Examine something to extract its meaning and express it in your own words
introduction	The first paragraph in sustained writing, offering a contention and an outline of the text
issue	A topic or question that is open to discussion, debate or dispute
justify	Provide clear reasons, grounds and evidence for a particular argument or conclusion
outline	Provide a basic overview of something, describing only its main features
paraphrase	To describe someone else’s words, statement or meaning, in your own words
review	Read or examine something and offer your own thoughts and judgements about it
signpost	Use phrases and sentences outlining the direction or structure your writing will take
summarise	Briefly describe the main points or attributes of something, without going into much detail

---

Citation information
Title: “History words”
Authors: Jennifer Llewellyn, Steve Thompson
Publisher: Alpha History
URL: https://alphahistory.com/history-words/
Date published: June 3, 2018
Date updated: December 24, 2022
Date accessed: April 12, 2023
Copyright: Content on this page may not be republished without our express permission. For more information on usage, please refer to our Terms of Use.

There are many word lists for general and academic English study. This page describes
the most important ones, first giving an
overview of the different types of word list, then presenting a
more detailed summary of individual lists.
The summary contains links to other pages on the site which have more detail of each list and (often) a complete copy of the list itself.

There is a companion page in this section which gives
information on why word lists are important (and tips on how to use them).

[Note: Links to other pages are in blue, links to other parts of this page are in red.]

Types of word list

Word lists can be divided into three types, namely
general word lists and
academic word lists, although as will be explained below, academic lists can be sub-divided into
general academic lists and
field-specific (i.e. subject-specific) academic lists.
An additional way to classify word lists is those which contain only single words (the majority of the lists are this type), and
multi-word lists. A final way to classify lists is written vs. spoken. Most of the lists that exist are
for written English, though many of the multi-word lists include both a spoken and written component.

General word lists (single words)

Interest in word lists began with studies of core or general vocabulary, that is, words having high frequency across a wide range of
texts. The first general word list to have important use in language study was the
General Service List (GSL), created by Michael West in 1953.
This list has been used to design EFL materials and courses, and, despite its age, it is probably still the most widely used list of general vocabulary.
Originally consisting of 2000 words (called headwords) and their corresponding word families, it was revised in 1995 by Bauman and Culligan,
with an increase in the number of headwords from 2000 to 2284.

One criticism of the GSL is its inclusion of too many low frequency words, some of which are a product of its age (e.g. shilling, headdress, cart, servant) while
excluding more recent vocabulary (e.g. computer, television, Internet). A second criticism is that it uses word families. The assumption behind the use of
word families is that once one word is known, other members of the family can be easily recognised; however, this may not always be the case. Examples of
distantly related word family pairs in the GSL are: please/unpleasantly, part/particle and value/invaluable. Additionally, some word
forms are used more frequently than others, and the inclusion of less frequent forms adds an unnecessarily burden to the learning load of students.

These criticisms have led to the creation of two updated versions of the list, both devised in 2013, both called the New General Service List.
Both lists use inflected forms and variant spellings (called lemmas), rather than extended word families.
The first, abbreviated to
NGSL, was developed by Browne, Culligan and Phillips. It is a list of 2801 words which give over 90% coverage.
It was generated from a corpus of 273 million words, 100 times larger than that used for the GSL.
The second list, abbreviated to
new-GSL, was devised by Brezina and Gablasova from a corpus of over 12 billion words.
It consists of 2494 words and gives around 80% coverage.

General word lists (multi-word)

The above are all single word lists. There are several multi-word lists for general vocabulary, such as the
First 100 Spoken Collocations (First 100) by Shin and Nation (2008), and the Phrasal Expressions List (PHRASE List) by Martinez and Schmitt (2012). However,
since none of these is used as a basis for academic word lists, in contrast to the general lists given above, they are not explained here in detail.

Academic word lists (single words)

Researchers have long been interested in defining and isolating academic vocabulary, and there have been many attempts to devise
lists which are of general use to students of academic English.

The first widely used academic word list was the
University Word List (UWL),
created in 1984 by Xue and Nation. It comprises 836 word families, divided into levels based on frequency.
It excludes words from the GSL, and gives 8.5% coverage of academic texts. It was developed by combining four existing lists.

A major update to the UWL came in 2000, when Averil Coxhead, of the University of Wellington, devised the
Academic Word List (AWL). This list
has been hugely influential and is perhaps the most widely known and used academic word list. Like the UWL, it comprises word families and is
divided into levels based on frequency. It gives similar coverage, around 10% of texts; however, it does so using far fewer word families, 570 in total.
Like the UWL, it excludes words from the GSL. It was devised in a more systematic way, using a corpus of texts from a range of academic disciplines.

Although the AWL is still widely used, it has received criticism in a number of areas. One criticism is that it is based on the
GSL, which is a very old list, dating from 1953. A second criticism is that, like the GSL, it uses word families, with the same problems as mentioned for
the GSL above.

In response to these criticisms, other academic word lists have been created. One of these is the
Academic Keyword List (AKL), developed by Paquot in 2010. This
consists of 930 words which appear more frequently in academic texts than non-academic ones, a tendency called keyness,
which leads to the name of the list.

A second list is the
New Academic Word List (NAWL) by
Browne, Culligan and Phillips. This list responds to the criticisms of the AWL by using lemmas rather than word families, and by basing itself on a more
updated general service list, the
NGSL, created by the authors at the same time, in 2013.

A third updated list is the
Academic Vocabulary List (AVL), developed by Gardner and Davies in 2013. This list, which is also lemma-based,
selects academic words by considering their ratio in academic versus non-academic texts, with words needing to occur 1.5 times as often in the
academic texts as in non-academic ones. This is similar to the approach used to devise the AKL (above), and in contrast to lists like the AWL and NAWL which
exclude an existing general service list. In addition, the authors considered the range of words in the academic disciplines used in their corpus,
the dispersion, and discipline measure, which required that words could not occur more than three times the expected frequency in any of
the disciplines. This approach has been influential in the development of other,
field-specific lists, as well as some
technical lists, as explained below.

There are several lists specifically for academic spoken English (as distinct from the spoken components of the multi-word lists, below).
These include the English Spoken Academic Wordlist, devised by Nesi in 2002,
the Academic Spoken Word List (ASWL), devised by Dang et al. in 2017, and
the Vocabulary for Academic Lecture Listening word list (VALL), devised by Thompson in 2015.

Academic word lists (multi-word)

Focusing exclusively on single words can lead learners to overlook valuable multi-word constructions which are commonly used in academic English.
For example, while use of the word thing is generally considered to be poor
academic style, it occurs in several phrases used by expert writers, such as
the same thing as and other things being equal.

Several multi-word lists have been developed for academic English. One is the
Academic Formulas List (AFL), devised by Simpson-Vlach and Ellis in 2009. This list
gives the most common formulaic sequences in academic English, i.e. recurring word sequences three to five words long.
There are three separate lists: one for formulas that are common in both academic spoken and written English (the ‘core’ AFL),
one for spoken English, and one for written English.

Another multi-word list is the
Academic Collocation List (ACL), developed by Ackermann and Chen in 2013. The ACL
contains 2469 of the most frequent and useful collocations which occur in written academic English.

A third list is the
Discourse Connectors List (DCL), devised by Rezvani Kalajahi, Neufeld and Abdullah in 2017. This list
classifies and describes 632 discourse connectors, ranking them by frequency in three different registers (academic, non-academic and spoken).

More recently, there is the
Academic idioms list, developed by Miller in 2019. This gives 170 idioms which are common in spoken academic
English, and 38 which are frequently used in written academic English.

Field-specific academic word lists (single words)

Academic word lists such as the AWL are designed to be used by students of all disciplines. Researchers have found, however, that the AWL and other lists
provide varied coverage in different subject areas. For example, the AWL provides 12.0% coverage of the Commerce sub-corpus used to derive the list,
but only 9.1% for the Science sub-corpus (with only 6.2% for Biology).
Additionally, words in the AWL (and similar lists) occur with different frequencies in different disciplines.
For example, words such as legal, policy, income, finance and legislate,
which all fall in the first (most frequent) sublist of the AWL, may be common in Business or Finance,
but are very infrequent in disciplines such as Chemistry.
Words also have different collocations and meanings across different subject areas. Examples are base, which has a special meaning in Chemistry,
and bug, which has a different meaning in Computer Science than in general English.

Researchers have therefore become increasingly interested in field-specific (i.e. subject-specific) academic lists, in disciplines ranging
from science to business to medicine. These are generally not
technical word lists, since they are intended to comprise academic (sub-technical) vocabulary.
However, not all of them set out to exclude technical words (some actually set out to include them), and even for those that do,
the line between academic and technical words is often blurred.

Broadly speaking, there are three approaches used by researchers when devising field-specific academic lists.

The first of these is to use the GSL and AWL as a starting point, and to devise a third list which supplements the other two. These lists
exclude GSL and AWL words, and, since they are based on word family lists, also comprise word families.
These lists usually replace the ‘A’ of ‘AWL’ with a subject specific letter.
Examples are the
SWL (Science Word List), the
BWL#1 (Business Word List #1), the
Pharmacology Word List and the
CSWL (Computer Science Word List).

The second approach is to assume that learners are already familiar with general vocabulary and to devise a second list which replaces
other academic lists such as the AWL or NAWL for specific subject areas. As such, these lists exclude the GSL (or NGSL), but do not
exclude any other lists such as the AWL.
These lists usually add the subject letter before ‘AWL’ to derive their name.
Examples are the
MAWL (Medical Academic Word List) and the
NAWL (Nursing Academic Word List), both of which exclude the GSL and are word family lists (like the GSL), and the
EAWL (Economics Academic Word List), which excludes the NGSL and is a lemma-based list (like the NGSL).

The third approach is to devise a single, completely independent list, which includes words based on ratio, dispersion, and other measures, in a similar
way the AVL. These lists, which are usually lemma-based, tend to use ‘AVL’ in their name, preceded by an abbreviation for the subject. Examples are the
MAVL (Medical Academic Vocabulary List) and the
CSAVL (Computer Science Academic Vocabulary List). The
Chemistry Academic Word List (CAWL), although it broadly uses
the same approach, uses word families, and also predates the creation of the AVL, and does not follow the same naming pattern.

There are two further lists which deserve mention here. Both have been developed using the same principles as the lists above; however, they
are intended for school-age rather than university students.

The first is the
Middle School Vocabulary Lists (MSVL). These are a series of five lists developed in 2015 by Greene and
Coxhead, along similar lines to Coxhead’s earlier AWL, i.e. by excluding the GSL and working with word families. However, this list is
intended not for students at or preparing for university, but middle school students, and covers technical rather than purely academic vocabulary.
The lists cover the following subjects: English, Health, Mathematics, Science, and Social Science/History.

Another is the
Secondary Schools Vocabulary Lists (SVL). Developed in 2018 by Green and Lambert, the SVL are a series of lists of
discipline-specific words for secondary school education, covering eight core subjects: Biology, Chemistry, Economics, English, Geology, History,
Mathematics, and Physics. The lists were devised using methods similar to those used to create the
AVL and the
MAVL, which are lemma-based lists which consider measures such as range and dispersion along with word frequency.
The lists also include word family versions, as well as collocation lists. The SVL are designed to help students in secondary schools improve their
disciplinary literacy.

There are at least two field-specific academic lists of spoken English, both devised by Dang in 2018. They are the Hard Science Spoken Word
List (HSWL), and the Soft Science Spoken Word List (SSWL).

Technical word lists (multi-word)

There have been some attempts to create discipline-specific multi-word lists, using principles employed in the creation of academic lists.
One is the Computer Science Multi-Word List (CSMWL), created by Minshall at the same time as the
Computer Science Word List (CSWL). However, it comprises only 23 items.

Another example is the
Secondary Phrase Lists (SPL), developed in 2018 by Green and Lambert, who also developed the SVL (above).
This is a series of lists, for the same eight subjects as covered by the SVL, presenting noun-noun, adjective-noun, noun-verb, verb-noun and verb-adverb
collocations.

A third, more recent example is the
Nursing Collocation List (NCL), developed in 2020 by Mandić and
Dankić. It comprises 488 collocations which occur frequently in nursing journal articles.

Summary

The following image, and table below, provide an overview of the major word lists. Spoken word lists are only included in the table
(in italics). All word lists (except spoken ones) are explained in more detail later. Note: there is a higher resolution copy of the following image in the
infographics section.

	Single word	Multi-word
General	• GSL (General Service List) 1953 • NGSL (New General Service List) 2013 • New-GSL (New General Service List) 2013	These exist, but none are used as a basis for academic lists.
Academic	• UWL (University Word List) 1984 • AWL (Academic Word List) 2000 • AKL (Academic Keyword List) 2010 • NAWL (New Academic Word List) 2013 • AVL (Academic Vocabulary List) 2013 • English Spoken Academic Wordlist 2002 • ASWL (Academic Spoken Word List) 2017 • VALL (Vocabulary for Academic Lecture Listening word list) 2015	• AFL (Academic Formulas List) 2009 • ACL (Academic Collocation List) 2013 • DCL (Discourse Connectors List) 2017 • Academic idioms list 2019
Field-specific/ technical	• SWL (Science Word List) 2007 • BWL#1 (Business Word List #1) 2007 • PWL (Pharmacology Word List) 2007 • MAWL (Medical Academic Word List) 2008 • AgroCorpus List 2009 • BEL (Basic Engineering List) 2009 • BWL#2 (Business Word List #2) 2011 • CSWL (Computer Science Academic Word List) 2013 • CAWL (Chemistry Academic Word List) 2013 • MAVL (Medical Academic Vocabulary List) 2015 • NAWL (Nursing Academic Word List) 2015 • EAWL (Environmental Academic Word List) 2015 • EAWL (Economics Academic Word List) 2019 • CSAVL (Computer Science Academic Vocabulary List) 2021 • MSVL (Middle School Vocabulary Lists) 2015 • SVL (Secondary School Vocabulary Lists) 2018 • HSWL (Hard Science Spoken Word List) 2018 • SSWL (Soft Science Spoken Word List) 2018	• CSMWL (Computer Science Multi-Word List) 2013 • SPL (Secondary Phrase Lists) 2018 • NCL (Nursing Collocation List) 2020

References

Granger, S., and Larsson, T. (2021), ‘Is core vocabulary a friend or foe of academic writing? Singleword vs multi-word uses of THING’, Journal of English for Academic Purposes, 52 (2021) 100999.

Hyland, K. and Tse, P. (2007). ‘Is There an “Academic Vocabulary”?’, TESOL QUARTERLY, Vol. 41, No. 2, June 2007.

Radmila Palinkašević, M.A. (2017), ‘Specialized Word Lists — Survey of the Literature — Research Perspective’, Research in Pedagogy, Vol. 7, Issue 2 (2017), pp. 221-238.

Therova, D. (2020), ‘Review of Academic Word Lists’, The Electronic Journal for English as a Second Language, Volume 24, Number 1.

Study the word list: history

for homework

	escape	He tried to escape from the cell.
	railroad	The slaves used the underground railroad. *
	conductor	The orchestra watched the conductor carefully.
	reward	There’s a big reward for his capture.
	route	We drove home by the scenic route.
	civil	You must speak to others in a civil manner.
	punishment	The judge handed out a harsh punishment to the criminal. *

* This sentence was added by a Spellzone user.

Use the list: history

Learn this spelling list using the ‘Look, Say, Cover, Write, Check‘ activity.

Spelling games using the word list: history

Test yourself using the ‘Listen and Spell‘ spelling test.

Print worksheets and activities using: history

Handwriting worksheets using: history