lexical density

The lexical density is the proportion of content words (lexical items) in a given discourse. It can be measured either as the ratio of lexical items to total number of words, or as the ratio of lexical items to the number of higher structural items in the sentences (for example, clauses).{{cite book|author=Erik Castello|title=Text Complexity and Reading Comprehension Tests|url=https://books.google.com/books?id=rYzvuQ5mHUcC&pg=PA48|year=2008|publisher=Peter Lang|isbn=978-3-03911-717-8|pages=49–51}}{{cite book|author=Belinda Crawford Camiciottoli|title=The Language of Business Studies Lectures: A Corpus-assisted Analysis|url=https://books.google.com/books?id=4S5ejvLhUtcC&pg=PA73|year=2007|publisher=John Benjamins Publishing|isbn=978-90-272-5400-9|page=73}} A lexical item is typically the real content and it includes nouns, verbs, adjectives and adverbs. A grammatical item typically is the functional glue and thread that weaves the content and includes pronouns, conjunctions, prepositions, determiners, and certain classes of finite verbs and adverbs.

Lexical density is one of the methods used in discourse analysis as a descriptive parameter which varies with register and genre. There are many proposed methods for computing the lexical density of any composition or corpus. Lexical density may be determined as:

::$L\_d\; =\; (N\_\{\backslash mathrm\{lex\}\}/N)\; \backslash times\; 100$

:Where:

::$L\_d$ = the analysed text's lexical density

::$N\_\{\backslash mathrm\{lex\}\}$ = the number of lexical or grammatical tokens (nouns, adjectives, verbs, adverbs) in the analysed text

::$N$ = the number of all tokens (total number of words) in the analysed text

{{Further |type-token distinction}}

Ure proposed the following formula in 1971 to compute the lexical density of a sentence:

::{{math|big=1| L_d {{=}} {{sfrac|The number of lexical items|The total number of words}} * 100 }}

Biber terms this ratio as "type-token ratio".{{cite book|author=Douglas Biber|title=Discourse on the Move: Using Corpus Analysis to Describe Discourse Structure|url=https://books.google.com/books?id=t4CcpizGwgQC |year=2007|publisher=John Benjamins Publishing|isbn=978-90-272-2302-9|pages=97–98 with footnote 7}}

In 1985, Halliday revised the denominator of the Ure formula and proposed the following to compute the lexical density of a sentence:

::{{math|big=1| L_d {{=}} {{sfrac|The number of lexical items|The total number of clauses}} * 100 }}

In some formulations, the Halliday proposed lexical density is computed as a simple ratio, without the "100" multiplier.

Lexical density measurements may vary for the same composition depending on how a "lexical item" is defined and which items are classified as lexical or as a grammatical item. Any adopted methodology when consistently applied across various compositions provides the lexical density of those compositions. Typically, the lexical density of a written composition is higher than a spoken composition. According to Ure, written forms of human communication in the English language typically have lexical densities above 40%, while spoken forms tend to have lexical densities below 40%. In a survey of historical texts by Michael Stubbs, the typical lexical density of fictional literature ranged between 40% and 54%, while non-fiction ranged between 40% and 65%.{{cite book|author1=Mark Warschauer|author2=Richard Kern|title=Network-Based Language Teaching: Concepts and Practice|url=https://books.google.com/books?id=wFH56QxG2uwC |year=2000|publisher=Cambridge University Press|isbn=978-0-521-66742-5|pages=107–108}}{{cite book|author=Michael Stubbs|title=Text and Corpus Analysis: Computer Assisted Studies of Language and Culture|url=https://books.google.com/books?id=2iAFIgAACAAJ|year=1996|publisher=Wiley|isbn=978-0-631-19512-2|pages=71–73}}

The relation and intimacy between the participants of a particular communication impact the lexical density, states Ure, as do the circumstances prior to the start of communication for the same speaker or writer. The higher lexical density of written forms of communication, she proposed, is primarily because written forms of human communication involve greater preparation, reflection and revisions. Human discussions and conversations involving or anticipating feedback tend to be sparser and have lower lexical density. In contrast, state Stubbs and Biber, instructions, law enforcement orders, news read from screen prompts within the allotted time, and literature that authors expect will be available to the reader for re-reading tend to maximize lexical density.{{cite book|author=Michael Stubbs|year= 1986|title= Talking about Text|chapter=Lexical density: A technique and some findings|editor=Malcolm Coulthard| publisher= University of Birmingham: English Language Research|pages= 27–42}} In surveys of lexical density of spoken and written materials across different European countries and age groups, Johansson and Strömqvist report that the lexical density of population groups were similar and depended on the morphological structure of the native language and within a country, the age groups sampled. The lexical density was highest for adults, while the variations estimated as lexical diversity, states Johansson, were higher for teenagers for the same age group (13-year-olds, 17-year-olds).{{cite journal|title=Lexical diversity and lexical density in speech and writing: a developmental perspective|author= Victoria Johansson|volume=53|year=2008|journal=Linguistics and Phonetics Working Papers|publisher=Lund University|pages=61–79}}{{cite journal|author1= Sven Strömqvist|author2= Victoria Johansson|author3=Sarah Kriz|author4=H Ragnarsdottir|author5=Ravid Aisenmann|author6=Dorit Ravid|author6-link=Dorit Ravid| year= 2002| title= Toward a crosslinguistic comparison of lexical quanta in speech and writing|journal = Written Language and Literacy|volume= 5|pages= 45–67|doi= 10.1075/wll.5.1.03str}}

• Content analysis
• Succinctness
• Information structure
• Peirce's type-token distinction

{{reflist}}

• Ure, J (1971). Lexical density and register differentiation. In G. Perren and J.L.M. Trim (eds), Applications of Linguistics, London: Cambridge University Press. 443–452.

• [http://textalyser.net Lexical density 'Textalyser']

Category:Computational linguistics

Category:Applied linguistics