4 Configurar túnel VPN
4.3 Túnel VPN entre SCALANCE S y CP
If the newsgroup texts lack grammatical intricacy, are they lexically dense like other written discourse? Lexical density is the relation between lexical and functional words per clause. The group of lexical words includes all adverbs, adjectives, nouns and verbs. All other words go into the functional word group, including cardinal and ordinal numbers as well as interjections. The PoS-tagged EDNA was thus divided into lexical and functional words. The
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total number for each word class as well as the percentages can be seen in table 4.4 below. Differences in the total number of the whole corpus as compared to total numbers in the TTR calculation are due to the fact that in the calculations of lexical density, the cardinal and ordinal numbers were included, whereas they were excluded in the TTR calculations. The deviation in numbers is smaller than 2% in both corpora, which is acceptable for the present study.
Word class EN GN
Lexical 5,344 51% 5,514 54% Functional 5,146 49% 4,707 46% Total 10,490 100% 10,221 100% Table 4.4 Lexical density in EDNA
The lexical density of the newsgroup texts can be compared to the numbers given in Halliday (1989a). Halliday (1989a, 80) states the following, referring to lexical words per clause:
[A] typical average lexical density for spoken English is between 1.5 and 2, whereas the figure for written English settles down somewhere between 3 and 6, depending on the level of formality in the writing.
In EN, the lexical density per clause is 3.39, in GN it is 3.68. The texts in EDNA are thus more closely related to written discourse, but located more towards less formal language in the continuum.
Another source, the Longman Grammar of Spoken and Written English (LGSWE) (Biber et al. 1999, 62), does not give percentages, except for two small text sam- ples of less than 100 words, but simply states that “[c]onversation has by far the lowest lexical density. News has the highest lexical density”. It is difficult to say whether the percentages of lexical and functional words in EDNA point towards high or low lexical density. There is, however, a statement in the LGSWE that is more useful: “The proportion of the lexical word classes varies with register: In conversation, nouns and verbs are about equally frequent. In news reportage and academic prose, there are three to four nouns per lexical verb” (Biber et al. 1999, 62).
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Table 4.5 shows that the ratio of noun-to-verb in the English texts is roughly 2:3. Clearly, the newsgroup texts are more similar to conversation in the LGSWE approach.
Word class EN
Nouns 1,453 14%
Lexical verbs 2,329 22% Other word class 6,708 64% Total corpus size 10,490 100%
Table 4.5 The noun-to-verb ratio in the English newsgroup texts
The numbers in table 4.5 above, however, are distorted. The newsgroup texts have been PoS-tagged with the BNC C5 tag set. The number in table 4.5 in- cludes all words tagged as lexical verbs, excluding only the modal auxiliaries. This is problematic, because some of the verbs, namely forms of be, have and do, can be used either as lexical verbs, or as primary auxiliaries, and the tags do not reveal how they were used. Here is an example:
(1) I’m 30, he’s 52. He’s been married twice.
I_PNP 'm_VBB 30_CRD ,_, he_PNP 's_VBZ 52_CRD ._. He_PNP 's_VHZ been_VBN married_VVN twice_AV0
The first two clauses have only one lexical verb (a form of to be), the third clause has a verbal group comprising three verbs; the forms of to have and to be function as primary auxiliary, married is the lexical verb. There is no indication of how the authors of the LGSWE dealt with the problem.
Another statement in the LGSWE is the following: “A high ratio of nouns to verbs corresponds to longer clauses and more complex phrases embedded in clauses” (Biber et al. 1999, 66). In the English newsgroup texts, the noun-to- verb ratio is low, thereby suggesting that the corpus consists of comparatively short clauses, with less complex phrases embedded in clauses. This again sug- gests the proximity of the newsgroup texts to conversation.
Let us look at the noun-to-verb ratio in the German newsgroup texts in table 4.6. The tag set used for German, i.e. the STTS tag set, does distinguish be-
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tween primary auxiliaries, lexical verbs and modal verbs (not included in the calculation here). Therefore, the numbers for the German noun-to-verb ratio were easier to calculate.
Word class GN
Nouns 1,352 13%
Lexical verbs 1,223 12% Auxiliary verbs 622 6% Other word class 7,024 69% Total size of corpus 10,221 100%
Table 4.6 The noun-to-verb ratio in the German newsgroup texts
The noun-to-verb ratio for the German newsgroup texts is almost exactly 1:1. If we assume that registers in German behave similar to their English counter- parts, the newsgroup texts are more like spoken than written discourse. The low noun-to-verb ratio implies that there are rather short clauses without complex embedded phrases. Comparing the English and German corpus, they have 14% and 13% nouns respectively, the English texts have slightly more verbs (22%) while the German texts have only 18% verbs (auxiliaries plus lexi- cal verbs, similar to the English counting). We can conclude that in the German texts, there are slightly more nouns per clause than there are in the English texts.
Feature Spoken dis-
course
Written dis- course
Grammatical intricacy (Halliday
1989a) X
Noun-to-verb ratio (Biber et al. 1999) X Lexical items per clause (Halliday
1989a) X
Figure 4.1 Categorisation of newsgroup texts
Figure 4.1 lists the three features investigated above and suggests that we can- not conclude once and for all whether the newsgroup texts are more like con- versation / spoken discourse or more like written discourse. The newsgroup texts seem to be a register that incorporates features from both.
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