View source for Word list

{{Short description|Bare list of a language's words in corpus linguistics}}
{{Citation style|date=March 2021}}
{{morefootnotes|date=December 2023}}
{{for|word lists used in word games|Scrabble#Acceptable words}}
{{use dmy dates|cs1-dates=ly|date=April 2021}}
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" ({{Harvnb|Nation|1997|p=}}), 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 (sociolinguistics)|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 processing|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 [[word]]s (word types) together with their [[frequency]], where frequency here usually means the number of occurrences in a given [[text corpus|corpus]], from which the rank can be derived as the position in the list.
{| class="wikitable" align="right"
! 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
|}
== Methodology ==
=== Factors ===
Nation ({{harvnb|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
=== Corpora ===
==== Traditional written corpus ====
[[File:Personal pronouns2.jpg|thumb|250px|upright|Frequency of [[personal pronoun]]s in [[Serbo-Croatian]]]]Most of currently available studies are based on written [[text corpus]], more easily available and easy to process.
==== SUBTLEX movement ====
However, {{harvnb|New|Brysbaert|Veronis|Pallier|2007}} proposed to tap into the large number of subtitles available online to analyse large numbers of speeches. {{harvnb|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,<ref name="subtlex-home">{{Cite web | url=http://crr.ugent.be/programs-data/subtitle-frequencies | title=Crr » Subtitle Word Frequencies}}</ref> providing valuable frequency count analysis for various languages. Indeed, the SUBTLEX movement completed in five years full studies for French ({{harvnb|New|Brysbaert|Veronis|Pallier|2007}}), American English ({{harvnb|Brysbaert|New|2009}}; {{harvnb|Brysbaert|New|Keuleers|2012|p= }}), Dutch ({{harvnb|Keuleers|New|2010|p= }}), Chinese ({{harvnb|Cai|Brysbaert|2010|p= }}), Spanish ({{harvnb|Cuetos|Glez-nosti|Barbón|Brysbaert|2011|p= }}), Greek ({{harvnb|Dimitropoulou|Duñabeitia|Avilés|Corral|Carreiras|2010|p= }}), Vietnamese ({{harvnb|Pham|Bolger|Baayen|2011|p= }}), Brazil Portuguese ({{harvnb|Tang|2012|p= }}) and Portugal Portuguese ({{harvnb|Soares|Machado|Costa|Iriarte|Simões|de Almeida|Comesaña|Perea|2015|p=}}), Albanian ({{harvnb|Avdyli|Cuetos|2013|p=}}), Polish ({{harvnb|Mandera|Keuleers|Wodniecka|Brysbaert|2014|p= }}) and Catalan (2019<ref>{{Cite journal |last1=Boada |first1=Roger |last2=Guasch |first2=Marc |last3=Haro |first3=Juan |last4=Demestre |first4=Josep |last5=Ferré |first5=Pilar |date=2020-02-01 |title=SUBTLEX-CAT: Subtitle word frequencies and contextual diversity for Catalan |journal=Behavior Research Methods |language=en |volume=52 |issue=1 |pages=360–375 |doi=10.3758/s13428-019-01233-1 |pmid=30895456 |s2cid=84843788 |issn=1554-3528|doi-access=free }}</ref>). SUBTLEX-IT (2015) provides raw data only.<ref name="SUBTLEX-IT">{{Cite web | url=https://osf.io/zg7sc/ | title=SUBTLEX-IT| date=7 January 2022| last1=Amenta| first1=Simona| last2=Mandera| first2=Paweł| last3=Keuleers| first3=Emmanuel| last4=Brysbaert| first4=Marc| last5=Crepaldi| first5=Davide}}</ref>
=== Lexical unit ===
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 "{{lang|fr|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.
=== Statistics ===
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) <math>N</math> of an item in the list using the [[binary logarithm|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.
:<math>N=\left\lfloor0.5-\log_2\left(\frac{\text{Frequency of this item}}{\text{Frequency of most common item}}\right)\right\rfloor</math>
where <math>\lfloor\ldots\rfloor</math> is the [[floor function]].
Frequency lists, together with [[semantic network]]s, are used to identify the least common, specialized terms to be replaced by their [[hypernym]]s in a process of [[semantic compression]].
=== Pedagogy ===
Those lists are not intended to be given directly to students, but rather to serve as a guideline for teachers and textbook authors ({{Harvnb|Nation|1997|p=}}). [[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" ({{harvnb|Nation|2006}}).
== Effects of words frequency ==
Word frequency is known to have various effects ({{harvnb|Brysbaert|Buchmeier|Conrad|Jacobs|Bölte|Böhl|2011|p= }}; {{harvnb|Rudell|1993|p= }}). Memorization is positively affected by higher word frequency, likely because the learner is subject to more exposures ({{harvnb|Laufer|1997}}). Lexical access is positively influenced by high word frequency, a phenomenon called [[word frequency effect]] ({{harvnb|Segui|Mehler|Frauenfelder|Morton1982|p= }}). The effect of word frequency is related to the effect of [[Age of Acquisition|age-of-acquisition]], the age at which the word was learned.
== Languages ==
Below is a review of available resources.
=== English ===
{{Further|Most common words in English}}
Word counting is an ancient field,<ref>{{Cite journal |last=Bontrager |first=Terry |date=1991-04-01 |title=The Development of Word Frequency Lists Prior to the 1944 Thorndike-Lorge List |url=https://doi.org/10.1080/0270271910120201 |journal=Reading Psychology |volume=12 |issue=2 |pages=91–116 |doi=10.1080/0270271910120201 |issn=0270-2711}}</ref> with known discussion back to [[Hellenistic]] time. In 1944, [[Edward Thorndike]], [[Irving Lorge|Irvin Lorge]] and colleagues<ref>{{Cite web |title=APA PsycNet |url=https://psycnet.apa.org/record/1945-00565-000 |access-date=2023-05-15 |website=psycnet.apa.org |language=en}}</ref> hand-counted 18,000,000 running words to provide the first large-scale English language frequency list, before modern computers made such projects far easier ({{harvnb|Nation|1997}}). 20th century's works all suffer from their age. In particular, words relating to technology, such as "blog," which, in 2014, was #7665 in frequency<ref>{{Cite web | url=http://www.wordandphrase.info/frequencylist.asp | title=Words and phrases: Frequency, genres, collocates, concordances, synonyms, and WordNet}}</ref> in the Corpus of Contemporary American English,<ref>{{Cite web | url=https://www.english-corpora.org/coca | title=Corpus of Contemporary American English (COCA)}}</ref> was first attested to in 1999,<ref>{{cite news|url=http://www.economist.com/surveys/displaystory.cfm?story_id=6794172|title=It's the links, stupid|publisher=The Economist|date=2006-04-20|access-date=2008-06-05}}</ref><ref>{{cite web|url=http://peterme.com/index.html|archive-url=https://web.archive.org/web/19991013021124/http://peterme.com/index.html|archive-date=1999-10-13|title=Peterme.com|last=Merholz|first=Peter|publisher=[[Internet Archive]]|year=1999|access-date=2008-06-05}}</ref><ref>{{cite web|url=http://www.kottke.org/03/08/its-weblog-not-web-log|last=Kottke|first=Jason|author-link=Jason Kottke|title=kottke.org|date=2003-08-26|access-date=2008-06-05}}</ref> and does not appear in any of these three lists.
;The Teachers Word Book of 30,000 words (Thorndike and Lorge, 1944)
The Teacher Word Book 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 ({{harvnb|Nation|1997}}).
;The [[General Service List]] (West, 1953)
The General Service List 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 ({{harvnb|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 ({{harvnb|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 ({{harvnb|Nation|1997}}).
=== French ===
;Traditional datasets
A review has been made by {{harvnb|New|Pallier}}.
An attempt was made in the 1950s–60s with the [[:fr:Français fondamental|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.<ref>{{cite web|url=http://pedagogie.ac-amiens.fr/casnav/accueillir/fle_fls/didactique/francais_fondamental.htm |title=Le français fondamental |url-status=dead |archive-url=https://web.archive.org/web/20100704172738/http://pedagogie.ac-amiens.fr/casnav/accueillir/fle_fls/didactique/francais_fondamental.htm |archive-date=4 July 2010 }}</ref> It is claimed that 70 grammatical words constitute 50% of the communicatives sentence,<ref>{{citation|title=Comprendre et aider les enfants en difficulté scolaire: Le Vocabulaire fondamental, 70 mots essentiels|last1=Ouzoulias|first1=André|publisher=Retz|year=2004|url=http://www.ac-caen.fr/ia50/circo/cou/IMG/pdf/70_mots_essentiels.pdf}} - Citing V.A.C Henmon (dead link, no Internet Archive copy, 10 August 2023)</ref><ref>[https://maternelle27.circonscription.ac-normandie.fr/IMG/pdf/70_mots_essentiels.pdf Liste des "70 mots essentiels" recensés par V.A.C. Henmon]</ref> while 3,680 words make about 95~98% of coverage.<ref>{{cite web|title=Generalities |url=http://www.riviere.info/vbr/livre/ch1generalites.htm}}</ref> A list of 3,000 frequent words is available.<ref>{{cite web|title=PDF 3000 French words |url=http://robert.riviere.info/download.php?op=mydown&did=4}}</ref>
The French Ministry of the Education also provide a ranked list of the 1,500 most frequent [[word family|word families]], provided by the lexicologue [[Étienne Brunet]].<ref>{{cite web |url=http://eduscol.education.fr/pid23250-cid50486/vocabulaire.html |title=Maitrise de la langue à l'école: Vocabulaire |publisher=Ministère de l'éducation nationale}}</ref> Jean Baudot made a study on the model of the American Brown study, entitled "Fréquences d'utilisation des mots en français écrit contemporain".<ref>{{citation|last1=Baudot|first1=J.|year=1992 |title=Fréquences d'utilisation des mots en français écrit contemporain|publisher=Presses de L'Université|isbn=978-2-7606-1563-2}}</ref>
More recently, the project [[Lexique3]] provides 142,000 French words, with [[orthography]], [[phonetic]], [[syllabation]], [[part of speech]], [[grammatical gender|gender]], number of occurrence in the source corpus, frequency rank, associated [[lexeme]]s, etc., available under an open license [[Creative Commons|CC-by-sa-4.0]].<ref>{{Cite web | url=https://chrplr.github.io/openlexicon/datasets-info/Lexique382/README-Lexique.html | title=Lexique}}</ref>
;Subtlex
This Lexique3 is a continuous study from which originate the [[#SUBTLEX movement|Subtlex movement]] cited above. {{harvnb|New|Brysbaert|Veronis|Pallier|2007}} made a completely new counting based on online film subtitles.
=== Spanish ===
{{Main|Most common words in Spanish}}
There have been several studies of Spanish word frequency ({{harvnb|Cuetos|Glez-nosti|Barbón|Brysbaert |2011}}).<ref>{{cite web|title=Spanish word frequency lists |website=Vocabularywiki.pbworks.com |url=http://vocabularywiki.pbworks.com/w/page/5254401/Spanish-word-frequency-lists}}</ref>
=== Chinese ===
Chinese corpora have long been studied from the perspective of frequency lists. The historical way to learn Chinese vocabulary is based on characters frequency ({{harvnb|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'' ({{harvnb|DeFrancis|1966}}).  As a frequency toolkit, Da ({{harvnb|Da|1998}}) and the Taiwanese Ministry of Education ({{harvnb|TME|1997}}) provided large databases with frequency ranks for characters and words. The [[Hanyu Shuiping Kaoshi|HSK]] list of 8,848 high and medium frequency words in the [[People's Republic of China]], and the [[Republic of China|Republic of China (Taiwan)]]'s [[Test of Proficiency-Huayu|TOP]] list of about 8,600 common traditional Chinese words are two other lists displaying common Chinese words and characters. Following the SUBTLEX movement, {{harvnb|Cai|Brysbaert|2010|p= }} recently made a rich study of Chinese word and character frequencies.
=== Other ===
Wiktionary:Frequency lists contains frequency lists in more languages.<ref>{{citation|url=https://en.wiktionary.org/wiki/Wiktionary:Frequency_lists|title=Wiktionary:Frequency lists|date=21 July 2024 }}</ref>
Most frequently used words in different languages based on Wikipedia or combined corpora.<ref>{{citation|url=http://www.ezglot.com/most-frequently-used-words.php|title=Most frequently used words in different languages|publisher=ezglot}}</ref>
== See also ==
* [[Letter frequency]]
* [[Most common words in English]]
* [[Long tail]]
* [[Google Ngram Viewer]] – shows changes in word/phrase frequency (and relative frequency) over time
== Notes ==
{{reflist}}
== References ==
{{Wiktionary|Wiktionary:Frequency lists}}
=== Theoretical concepts ===
* {{citation|last=Nation |first=P.|editor1-last=Schmitt |editor2-last= McCarthy |title = Vocabulary: Description, Acquisition and Pedagogy |chapter= Vocabulary size, text coverage, and word lists |place= Cambridge |publisher= Cambridge University Press |year=1997 |pages=6–19 |isbn=978-0-521-58551-4 |chapter-url=http://www.lextutor.ca/research/nation_waring_97.html}}
* {{citation|last1=Laufer |first1=B. |year=1997 |chapter=What’s in a word that makes it hard or easy? Some intralexical factors that affect the learning of words. |title=Vocabulary: Description, Acquisition and Pedagogy |isbn=9780521585514 |publisher=Cambridge University Press|place=Cambridge|pages=140–155}}
* {{citation|last=Nation |first=P. |author-link=Paul Nation |year=2006 |title=Language Education - Vocabulary |journal=Encyclopedia of Language & Linguistics |place=Oxford |pages=494–499 |doi=10.1016/B0-08-044854-2/00678-7 |isbn=9780080448541}}.
* <!--{{harvnb|Brysbaert|Buchmeier|Conrad|Jacobs|Bölte|Böhl|2011|p= }}-->{{cite journal|last1=Brysbaert |first1=Marc |last2=Buchmeier|first2=Matthias|last3=Conrad|first3=Markus|last4=Jacobs|first4=Arthur M. |last5=Bölte|first5=Jens |last6=Böhl|first6=Andrea|year=2011 |title=The word frequency effect: a review of recent developments and implications for the choice of frequency estimates in German|journal=Experimental Psychology |volume=58|issue=5|pages=412–424 |doi=10.1027/1618-3169/a000123|pmid=21768069 |url=http://crr.ugent.be/papers/The%20word%20frequency%20effect%20and%20German%20final%20version.doc}} [http://crr.ugent.be/SUBTLEX-DE/ database]
* <!--{{harvnb|Rudell|1993|p= }}-->{{citation|last1=Rudell|first1=A.P. |year=1993 |chapter=Frequency of word usage and perceived word difficulty : Ratings of Kucera and Francis words|title=Most|volume=25|issue=4 |pages=455–463}}
* {{citation|last1=Segui|first1=J. |first2=Jacques|last2=Mehler|first3=Uli|last3=Frauenfelder|first4=John |last4=Morton |year=1982 |title=The word frequency effect and lexical access |journal=Neuropsychologia |volume=20 |issue=6 |pages=615–627 |doi=10.1016/0028-3932(82)90061-6 |pmid=7162585 |s2cid=39694258 |url=https://archive-ouverte.unige.ch/unige:83838}}
* {{citation|last=Meier |first=Helmut |year=1967 |title=Deutsche Sprachstatistik |place=Hildesheim |publisher=Olms}} (frequency list of German words)
* {{citation|last=DeFrancis|first=John|year=1966|title=Why Johnny can't read Chinese}}
* {{citation|last=Allanic|first=Bernard|title=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) |url=http://www.theses.fr/2003INAL0006|year=2003|place=Paris|publisher=INALCO|type=These de doctorat}}
=== Written texts-based databases ===
* {{citation|last1=Da|first1=Jun|year=1998|title=Jun Da: Chinese text computing |url= http://lingua.mtsu.edu/chinese-computing/statistics/ |access-date=21 August 2010}}.
* {{citation|author=Taiwan Ministry of Education|ref={{harvid|TME|1997}}|year=1997|title=八十六年常用語詞調查報告書|url=http://www.edu.tw/files/site_content/M0001/86news/ch2.html?open |access-date=21 August 2010}}.
* {{citation|last1=New|first1=Boris|last2=Pallier|first2=Christophe|edition=3.01|title=Manuel de Lexique 3 |language=fr |url=http://www.lexique.org/outils/Manuel_Lexique.htm#_Toc152122347}}.
* {{citation|last1=Gimenes|first1=Manuel|last2=New|first2=Boris|title=Worldlex: Twitter and blog word frequencies for 66 languages|journal=Behavior Research Methods|year=2016|volume=48|number=3|pages=963–972|issn=1554-3528 |doi=10.3758/s13428-015-0621-0 |pmid=26170053 |doi-access=free}}.
=== SUBTLEX movement ===
* <!-- {{harvnb|New|Brysbaert|Veronis|Pallier|2007|p= }}-->{{cite journal|last1=New|first1=B. |last2=Brysbaert|first2=M.|last3=Veronis|first3=J.|last4=Pallier|first4=C.|year=2007 |title=SUBTLEX-FR: The use of film subtitles to estimate word frequencies|journal=Applied Psycholinguistics|volume=28|issue=4 |pages=661 |url=http://sites.univ-provence.fr/veronis/pdf/2007-AppliedPsy.pdf|archive-url= https://web.archive.org/web/20161024001257/http://sites.univ-provence.fr/veronis/pdf/2007-AppliedPsy.pdf |archive-date=2016-10-24 |doi=10.1017/s014271640707035x|hdl=1854/LU-599589|s2cid=145366468 |hdl-access=free}}
* <!--{{harvnb|Brysbaert|New|2009|p= }}-->{{citation|last1=Brysbaert|first1=Marc|first2=Boris|last2=New |year=2009 |title=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|journal=Behavior Research Methods|volume=41|issue=4|pages=977–990 |doi=10.3758/brm.41.4.977|pmid=19897807|s2cid=4792474 |url=http://expsy.ugent.be/subtlexus/Brysbaert%26NewBehaviorResearchMethods.pdf|doi-access=free}}
* <!--{{harvnb|Keuleers|New|2010|p= }}-->{{citation|last1=Keuleers|first1=E, M, B. |last2=New|first2=B. |year=2010 |title=SUBTLEX--NL: A new measure for Dutch word frequency based on film subtitles |journal=Behavior Research Methods |volume=42|issue=3|pages=643–650|pmid=20805586 |doi=10.3758/brm.42.3.643 |doi-access=free |url=http://crr.ugent.be/programs-data/subtitle-frequencies/subtlex-nl}}
* <!--{{harvnb|Cai|Brysbaert|2010|p= }}-->{{citation|last1=Cai|first1=Q.|last2=Brysbaert|first2=M. |year=2010|title=SUBTLEX-CH: Chinese Word and Character Frequencies Based on Film Subtitles|journal=PLOS ONE |volume=5 |issue=6 |pages=8 |doi=10.1371/journal.pone.0010729 |pmc=2880003 |pmid=20532192 |bibcode=2010PLoSO...510729C|doi-access=free}}
* <!--{{harvnb|Cuetos|Glez-nosti|Barbón|Brysbaert|2011|p= }}-->{{citation |last1=Cuetos |first1=F. |first2=Maria |last2=Glez-nosti |first3=Analía |last3=Barbón |first4=Marc |last4=Brysbaert |year=2011 |title=SUBTLEX-ESP : Spanish word frequencies based on film subtitles |journal=Psicológica |volume=32 |pages=133–143 |url=http://www.uv.es/psicologica/articulos2.11/1CUETOS.pdf}}
* <!--{{harvnb|Dimitropoulou|Duñabeitia|Avilés|Corral|Carreiras |2010|p= }}-->{{citation |last1=Dimitropoulou|first1=M.|first2=Jon Andoni|last2=Duñabeitia|first3=Alberto|last3=Avilés|first4=José |last4=Corral |first5=Manuel |last5=Carreiras |year=2010 |title=SUBTLEX-GR: Subtitle-Based Word Frequencies as the Best Estimate of Reading Behavior: The Case of Greek |journal=Frontiers in Psychology|volume=1 |issue=December|pages=12 |doi=10.3389/fpsyg.2010.00218|pmid=21833273|pmc=3153823|doi-access=free}}
* <!--{{harvnb|Pham|Bolger|Baayen|2011|p= }}-->{{citation|last1=Pham|first1=H.|last2=Bolger|first2=P. |last3=Baayen|first3=R.H. |year=2011 |title=SUBTLEX-VIE : A Measure for Vietnamese Word and Character Frequencies on Film Subtitles|journal=ACOL}}
* <!--{{harvnb|Brysbaert|New|Keuleers|2012|p= }}-->{{citation|last1=Brysbaert|first1=M.|last2=New |first2=Boris|last3=Keuleers|first3=E.|year=2012 |title=SUBTLEX-US : Adding Part of Speech Information to the SUBTLEXus Word Frequencies|journal=Behavior Research Methods|pages=1–22 |url=http://crr.ugent.be/papers/Adding%20Part%20of%20Speech%20information%20to%20the%20SUBTLEX-US%20word%20frequencies.pdf}} ([http://expsy.ugent.be/subtlexus/ databases])
<!-- -->
* <!--{{harvnb|Mandera|Keuleers|Wodniecka|Brysbaert|2014|p=471–83 }}-->{{cite journal |pmid=24942246 |doi=10.3758/s13428-014-0489-4 |volume=47 |issue=2 |title=Subtlex-pl: subtitle-based word frequency estimates for Polish |year=2014 |journal=Behav Res Methods |pages=471–483 |last1=Mandera |first1=P. |last2=Keuleers |first2=E. |last3=Wodniecka |first3=Z. |last4=Brysbaert |first4=M.| s2cid=2334688 |url=http://crr.ugent.be/papers/subtlex-pl.pdf}}
* <!--{{harvnb|Tang|2012|p=}}-->{{citation|last=Tang|first=K.|year=2012|title=A 61 million word corpus of Brazilian Portuguese film subtitles as a resource for linguistic research|journal=UCL Work Pap Linguist |issue=24 |pages=208–214}}
* <!--{{harvnb|Avdyli|Cuetos|2013|p=}}-->{{citation|last1=Avdyli|first1=Rrezarta|last2=Cuetos |first2=Fernando|date=June 2013|title=SUBTLEX- AL: Albanian word frequencies based on film subtitles |journal=ILIRIA International Review |volume=3|number=1|pages=285–292|issn=2365-8592 |doi=10.21113/iir.v3i1.112 |doi-broken-date=1 November 2024 |doi-access=free |url=http://www.iliriapublications.org/index.php/iir/article/download/112/104}}
* <!--{{harvnb|Soares|Machado|Costa|Iriarte|Simões|de Almeida|Comesaña|Perea|2015|p=}}-->{{citation |date=April 2015|journal=The Quarterly Journal of Experimental Psychology|volume=68|issue=4|pages=680–696|first1=Ana Paula |last1=Soares|first2=João|last2=Machado|first3=Ana|last3=Costa|first4=Álvaro |last4=Iriarte|first5=Alberto|last5=Simões|first6=José João|last6=de Almeida|first7=Montserrat |last7=Comesaña|first8=Manuel |last8=Perea|title=On the advantages of word frequency and contextual diversity measures extracted from subtitles: The case of Portuguese |doi=10.1080/17470218.2014.964271|pmid=25263599|s2cid=5376519}}
{{Frequency list}}
{{list of lists |language |listcat=Language acquisition |sort=Word lists}}
{{DEFAULTSORT:Word lists by frequency}}
[[Category:Quantitative linguistics]]
[[Category:Computational linguistics]]
[[de:Häufigkeitsklasse]]
[[hy:Հաճախականության բառարաններ]]