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Language of Wordsworth and his predecessors: ‘Objective’ reality of ‘difference myth’

(unpublished)

Md. Jahurul Islam

NC State University, Raleigh

Wordsworth’s explicit claim in favor of his poetic diction’s being simpler and less

complex in relation to contemporary popular poets, has been of much interest to the readers and

literary critics. Traditionally the perception of the level of linguistic complexity, in prose as well

as poetry, descends from our subjective judgment which is susceptible to the individual

backgrounds of people. Keeping this in mind, this study sought to answer the question of

linguistic complexity in Wordsworth’s poetry in contrast to three other contemporary poets by

means of employing ‘text analytic’ tools and techniques from digital humanities.

This paper is organized in five major sections. The first section gives a little background

of the research problem. In the second section, I have enlisted the specific objectives of the

study. The next section is a description of the methodology adopted in this study. The fourth

section presents and explains the results derived from the analysis. The final section summarizes

the findings of the study and delineates the conclusions based on the analysis of the results.

INTRODUCTION

Wordsworth, in his Preface to the Lyrical Ballads, claims that his ‘experimental poetry’ is

significantly different from that of his predecessors. He overtly criticizes the contemporary

literary trends, and claims that the language of the earlier poets was full of artificial so-called

‘poetic diction’, which puts the readers at the ‘mercy of the writers’ (Wordsworth 647).

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However, comments from some critics (e.g. Griffin) indicate that the difference claimed

by Wordsworth is more of a myth than reality. As Griffin points out, Wordsworth’s rejection of

the literary practices of his predecessors, especially the literary language of Pope, was much

more an explicit “emphatic denial” (699). To pave the way for his newer kind of poetry against

the then popular trends of poetry by Pope, Dryden and others, Wordsworth chose to downgrade

the others. However, as Griffin contends, there was an underlying current of influence of Pope

going on Wordsworth’s writings, in spite of the outright rejection of Pope by Wordsworth: “Pope

represents for Wordsworth a literary ‘family of origin’” (699). Wordsworth was preoccupied

with the notion of keeping away from Pope. In Wordsworth’s claim, the language of his new

poetry in the Lyrical Ballads is ‘a selection of the real language of men’, in opposition to the

‘poet-produced language’ of the earlier poets.

Conventionally we rely entirely on our subjective interpretations to determine the degree

of complexity of the language employed by a writer. Often the interpretations are prone to be

influenced by the linguistic background of the person and the degree of exposure to the particular

genre of writing; and this is why different people might come up with different judgments about

the degree of linguistic complexity of the same piece of writing. The task becomes hazier when

we are to compare a number of writers at the same time because we do not have any set of

standardized categories to grade different degrees of linguistic complexity.

Quantitative measures of linguistic complexity might be a potentially useful alternative

solution to this problem. These measures might effectively be used to objectively determine the

degree of complexity of the language of any given text, irrespective of its length; more usefully,

they can be used to compare the degree of complexity between the works of multiple writers

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because the quantitative results would generate values corresponding to the continuum of

complexities.

OBJECTIVES

This paper attempts an objective investigation, employing text analytic tools, of Wordsworth’s

poetic diction in the light of his predecessors, more particularly Pope, Burns, and Gray. In

particular, this study will make an objective evaluation of the language in Wordsworth’s poetry

in contrast to that in Pope’s, Burns’ and Gray’s, with a view to examining how different

Wordsworth’s language is from the others.

METHOD

Unlike the most popular means of literary analysis, which is primarily subjective in nature, this

study incorporates the use of quantitative methods as a means for assisting critical evaluation of

the literary text. Basically, the quantitative methods derive from the area of digital humanities, a

part of which is ‘text analysis’ and ‘text-mining’ with the employment of modern computational

tools.

Tools employed in the study

The statistical software “R” (R Core Team 2013) was used as the primary tool for processing the

words and lexemes of the texts concerned; the same tool was used for analyzing different

patterns in the text organization and run statistical tests. The R-packages ‘ggplot2’ (Wickham

2009) and ‘gridExtra’ (Auguie 2012) were used for plotting the results into graphs, when

feasible.

The corpus

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Any Text Analytic venture requires a corpus which is available in digitized format; a TEI

encoded version, which follows a set of standardized rules for structuring the encoded text data,

would always be preferable to any other digitized versions of a text. Another challenge is to find

the texts of interest stacked together in a single place, since it is very difficult to build a corpus,

which might itself contain hundreds of pieces of works, by collecting them as fragments from

different sources and put them together. Therefore, in the absence of TEI encoded texts, this

study took all of the texts from the Project Gutenberg archive (Project Gutenberg) which has

made works of different writers available in different formats including ‘Plain Text UTF-8’

format, which is convenient for text processing.

The custom corpus for this study included poetical works by four poets: William

Wordsworth, Alexander Pope, Robert Burns and Thomas Gray. For Wordsworth, there were

fifty-six poems from the Lyrical Ballads (1800 edition) as available in the two volumes (Lyrical

Ballads with Other Poems, 1800 Volume I, and Volume II) in Project Gutenberg archive; the four

poems by Coleridge were excluded from the Lyrical Ballads. Pope’s poems were taken from the

first volume of Pope’s poetical works (The Poetical Works of Alexander Pope, Volume I). The

volume of the collected works for Burns in Gutenberg collection (Poems and Songs of Robert

Burns) included both poems and songs, and so a selection of the poems were chosen; the songs

were excluded from the corpus and the total number of poems for Burns in the corpus was

ninety. Gray had the lowest number of poems in the corpus; all of his seven poems in the

Gutenberg collection (Select Poems by Thomas Gray) were included in the corpus. Following is

a summary of the number of poems for each writer in the corpus (see table 1; for the titles of all

the poems, see Appendix).

Table 1

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Poets and the number of poems in the corpus

Poets Wordsworth Pope Burns Gray

Number of poems 56 38 90 07

Text processing

Since the raw texts of the corpus were not suitable to be ‘read’ into ‘R’, some additional

encodings were done manually to format and structure the texts in a patterned way. Then the

words of the individual poets were processed in R, and word frequency tables, which contained

how many times each of the words occurs in the individual texts, were generated to compare the

vocabularies used by the different poets. Primarily, the frequency tables excluded the stop words,

which commonly refers to the ‘articles’, ‘determiners’, ‘prepositions’, ‘conjunctions’, and so on.

Generally, these words are excluded on the presumption that they occur very frequently, but do

not contribute much to the core meaning of the texts.

After processing the texts, quantitative analysis of the word lists were performed to

compare the words used by individual poets. The techniques employed included Comparing the

vocabulary, Token distribution analysis, Lexical variety/Vocabulary richness, Lexical diversity,

and so on. Illustrations of each of the terms will follow in the respective sections that report their

results.

RESULTS

Comparing the vocabulary

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A useful way of comparing the languages of different poets is to compare the very words used by

them in order to find if there are any consistent patterns. With such intentions, this section takes

interest in the following: the comparison of the working vocabularies with the number of total

tokens, the extent of overlaps in the vocabularies, the most frequent words for each poet,

correlation between the number of total tokens and the number of word-types. These terms have

been explained in detail in the following sections.

‘Number of total tokens’ vs. ‘working vocabulary’ for individual poets

A preliminary look at the number of total tokens (henceforth ‘NTT’) used by the poets (see table

2) might reveal some overall generalizable patterns.

Table 2

Number of total tokens and size of working vocabulary for Individual Poets (excluding stop

words)

1

Number of total tokens

(NTT)

2

Number of word-types

(NWT or WV)

Wordsworth 15368 4346

Pope 33083 7996

Burns 22802 7560

Gray 2370 1564

As for the columns in table 2, ‘number of total tokens’ refers to the accumulated total

occurrences of all words (including the repetitions of any word), and ‘number of word-types’

(henceforth ‘NWT’) is the total number of individual ‘words’ (disregarding their repetitions)

used in the texts. And since NWT refers to the stock of vocabulary for a poet, the term has been

used interchangeably with WV, meaning ‘working vocabulary’.

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A quick glance of the table above indicates that Wordsworth has used considerably lower

number of words in relation to Pope and Burns. NWTs for the poets indicate that Wordsworth

has a smaller reserve of WV than Pope and Burns. Pope and Burns have nearly same size of WV

in spite of the difference between their numbers of total tokens. However, there seems to be a

potentially remarkable influence of the total size of the corpus for the poets and the size of their

WV. Though Gray is apparently the poet who has the lowest WV, it seems to happen only due to

the much smaller size of the corpus for him. Therefore, though the small corpus of Gray’s work

might, on the first look, seem to be insignificant to have been included in the study, it helps us

formulate a hypotheses that ‘as the NTT increases, the size of the WV for the poet also

increases’. This very hypothesis will be investigated more deeply in correlation between NTT

and NWT section.

How much of Wordsworth’s vocabulary match with that of Pope, Gray and Burns?

As for the extent of the shared vocabularies (see table 3), we can find some interesting patterns.

Wordsworth and Pope has 2541 words in common which is 58% of Wordsworth’s and 32% of

Pope’s WVs. Compared together, Wordsworth, Pope and Burns have 1771 words in common

which refers to 42% words of Wordsworth, 22% of Pope and 23% of Burns. We can see a kind

of consistency between Pope and Burns in terms of the percent of their WVs they share. They

were consistent in case of words they shared between them, as well: 41% of Pope’s vocabulary

matched with 43 percent of Burns’. This indicates to the possibility that the working

vocabularies for the poets other than Wordsworth have greater extent of match between them.

This might, therefore, be interpreted as an indication that Wordsworth’s WV has higher degree

of deviance from the WVs of the other three, and also that Pope, Burns and Gray share greater

range of vocabularies between them, than with Wordsworth.

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Table 3

Working vocabulary match between poets:

Poet combination Raw count of word

matches Percent of WV

Wordsworth-Pope 2541 58% of Wordsworth

32% of Pope

Wordsworth-Pope-Burns 1771

42% of Wordsworth

22% of Pope

23% of Burns

Wordsworth-Pope-Burns-Gray 701

16% of Wordsworth

9% of Pope

9% of Burns

45% of Gray

Pope-Burns 3246 41% of Pope

43% of Burns

Which are the most frequent words used by the poets?

So far, we have considered raw frequency measures (counting how many times individual words

occur in a text and take the cumulative total) of the words for individual poets in the corpus.

However, to study and compare the patterns of how frequently the words occur in a text, raw

frequency measures are of little help due to the differences in the sizes of works for different

poets in the corpus; obviously we can hardly expect the sizes of writings by different poets to be

exactly the same. Using relative frequency measures offers a better alternative; a ‘relative

frequency value’ would refer to the percentage of the occurrence of a specific word in relation to

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the total number of words in the text/poet. The basic advantage of using relative frequency

values is that it makes the measures directly comparable across authors.

Plotting the relative frequency values for all the words for each of the poets might help us

form an overall idea of how the frequencies are distributed for different words; in other words,

we are asking if all the words in the WV of an poet occur at the same rate, or a different rate. As

we can observe (see fig. 1 to 4, each point refers to a word, and y-axis indicates the frequency of

the word), the highest occurring words for each of the poets are considerably smaller in relation

to the size of the WV. Only a handful number of words get recycled at a significantly higher rate.

Fig. 1. Relative frequency of all words for Wordsworth (4346 words)

Fig. 2. Relative frequency of all words for Pope (7996 words)

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Fig. 3. Relative frequency of all words for Burns (7560 words)

Fig. 4. Relative frequency of all words for Gray (1564 words)

Now, the top ten words (the ones having the highest relative frequency values) of each of

the poets were plotted to compare the patterns, along with their range of relative frequency

values; and it produces interesting patterns (see fig. 5).

It is remarkable that the word ‘man’ turns out to be the most frequently used word for

three of them: Wordsworth, Pope and Burns. However, Wordsworth has a higher tendency of

using ‘man’ over the other two. Also, both Wordsworth and Burns have the words ‘day’ and

‘poem’ in the top ten words; but Pope does not have any more words common with Burns.

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Fig. 5. Top ten words and their relative frequencies (all poets)

Another fact from the plots draws our attention that at least four of the ten words (‘sae’,

‘wha’, ‘hae’, ‘nae’) for Burns are not usual English words, even if we consider the period of

Wordsworth. A possible explanation for the occurrences of such words might be that Burns was

actually from Scotland, which might have had some influence on his vocabularies. An evidence

in support of this claim could be substantiated by the occurrence of similar words in the “Scots

Wha Hae”, which “used to be considered Scotland’s national anthem (Scots Wha Hae, 2013).

Interestingly, even some recent Scottish writings show such use of words (e.g. Hodgart 1997).

To summarize the findings above, Wordsworth does not seem to be significantly different

from the other poets in relation to the ratio of highly recycled words; the great majority of words

in the WV for each poet lie below the relative frequency value of 0.05. However, the highest

occurring words have a higher range for Wordsworth than for the others; in other words,

Wordsworth has a higher range of relative frequency values than any other poets here. Therefore,

it might be conjectured that Wordsworth intended to bring about a sense of difference in this

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language by recycling a small range of words (may be the popular words like ‘man’, ‘day’,

‘heart’) more frequently than the others.

Correlation between the ‘NTT’ and the ‘NWT’

This section examines if there is any difference between the poets regarding the degree of

correlation between the NTT and the NWT in the poems. ‘Correlation’ is a statistical concept,

expressed as a value between 0 and 1, which indicates the relationship between two series of

values. A higher value, conventionally termed as ‘correlation coefficient’, is indicative of greater

degree of dependence between the two variables. The coefficient can be either positive or

negative: a positive value means that if one of the variable increases, the other also increases,

while a negative value means that one variable decreases if the other is increased.

Now, the two variables put to the test of correlation in our case were the NTT and the

NWT in each of the poems by a poet. The intention was to see if the NWT increases when the

NTT increases. Results show a pretty interesting pattern (see fig. 6): the correlation was very

high for all the poets; but, Wordsworth and Pope had a lower degree of correlation in contrast to

Burns and Gray. And, the difference between Wordsworth and Pope and between Burns and

Gray were pretty close.

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Fig. 6. Correlation between NTT and NWT for all poets

It is, however, to be kept in mind that we need to ensure, according to the conventional

statistical principles, that the results on which our interpretation relies are not due to any chance

or accidents (one single test of correlation might sometimes be so). To prevent us from this

potential problem, the same test of correlation was performed 5000 times iterative for each poet,

each time with a different subset (consisting of randomly chosen 90% values of the corpus for an

author) of the whole corpus for each poet.

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Fig. 7. Results of correlation between NTT and NWT (5000 iterations)

From the results of the tests (see fig. 7), we can now confidently conclude that

Wordsworth and Pope had consistently lower correlation than Burns and Gray (which can be

vindicated from the mean value (vertical dashed line) of the distributions. Wordsworth and Pope

had nearly similar degree of correlation between the NTT and the NWT. So, in this case,

Wordsworth deviated considerably from Burns and Gray, but was similar to Pope.

Token distribution analysis

Token distribution analysis is basically preoccupied with investigating the distribution of the

word-types in the work of an author. A balance distribution of the token throughout a piece of

writing indicates a constant level of complexity, while an imbalanced distribution would indicate

that different portions of the text are of different levels of complexity.

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To study the distribution of the words in the works of the poets concerned, this section

attempts to examine the rate of introducing new pieces of vocabulary as the corpus grows in size

and the distribution of the WV for each speaker in different quarters of their corpus.

Rate of introducing new words as a function of length of corpus

Examining the rate of introducing new/unique words might reveal how fast an author introduces

the readers to his WV. The corpus for each of the poets was divided into four quarters, and a

function was developed to calculate the number of the words-first-ever-in-the-corpus in each

quarter. The total number of such words were then converted into the percentage in relation to

the size of the poet’s WV, and plotted in a graph.

Fig. 8. Rate of introducing new words in relation to corpus length

The steeper slope between quarter 1 and 2 for Wordsworth (see fig. 8), in contrast to the

other poets, indicates that Wordsworth introduced his WV to the reader at a considerably high

pace. He introduced almost 45% of his WV in the first quarter of his corpus; and in the

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remaining three quarters, he continues to recycle the already introduced words. The other three

poets have relatively steady decrease in the number of newly introduced words in different

quarters.

Distribution of the WV throughout the whole corpus

Another useful way to investigate the distribution of tokens to each poet is to examine the rate of

words (from the WV) used in each quarter. To be more specific, it means to see the number of

words (in percentage) from the WV in each of the quarters.

Fig. 9. Number of words from WV in each quarter (in percent)

Results (see fig. 9) show different patterns for each poet: Burns and Wordsworth had an

overall upward trend; Gray had a relatively flat trend, while Pope had a curve-like trend. The

interesting pattern here seems to be that Wordsworth and Burns had consistently high percentage

values (higher than 35 %) than Pope and Gray. Also, values for Pope were consistently near or

below 30. The take away from these results might be that Wordsworth (also Burns) had a pretty

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higher rate of recycling words from his WV throughout his corpus, than Pope’s (and Gray’s) rate

of recycling words.

Lexical variety/Vocabulary richness

The measures of lexical variety, which can also be called ‘vocabulary richness’, contribute to the

level of linguistic complexity in a given piece of writing. To investigate the degree of linguistic

complexity in a quantitative method, Jockers introduces some ways to measure lexical variety to

vocabulary richness, which include ‘Type-Token Ratio’ and ‘Mean Word Frequency’ (61). We

will investigate all these two measures in the following section.

Type-token Ratio

Type-Token Ratio (henceforth, ‘TTR’) refers to the ratio between the NWT and the NTT used by

an author. To generate the TTR value, the NWT is divided by the NTT, and then the result is

multiplied by 100 to obtain a value in percentage. As for how to interpret the value, ‘a lower

TTR is suggestive of less lexical variety’ (Jockers 61).

Fig. 10. TTR for each poet

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Comparison of the TTR values for each of the poets (fig. 10) revealed a very interesting

pattern. Firstly, there seemed to be two clusters, one with Wordsworth and Pope and other with

Burns and Gray, which were away from one another. Moreover, Pope was ranked lower than

Wordsworth, which is quite against general assumptions following the claims of Wordsworth

himself in his Preface that his language is ‘simpler’ than Pope and others. Wordsworth was

surely a lot less complex than Burns and Gray, but it was the reverse in case of Pope. To look at

this same concept, we can now examine the mean word frequency for each poet.

Mean word frequency

Mean word frequency is, in principle, the same thing as TTR looked from another point of view.

Though they are derived from the same mathematical measures, mean word frequency interprets

the results from different angle which might be of interest. We can calculate mean word

frequency by dividing the NTT by the NWT. In principle, the mean word frequency value is a

measure of how many times, on average, each of the words in the corpus has been used. And, by

comparing the mean word frequency values for different writers, we can have an idea of the

degree to which the writers recycle their words (in opposition to introducing new vocabularies

again and again); a higher measure would indicate higher rate of vocabulary recycling.

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Fig. 11. Mean word frequency for each poet

Results (fig. 11) indicated, as expected, the same pattern we found in case of TTR values.

The only difference was that the relations of the poets were now reverse, with Pope at the top

followed by Wordsworth, Burns and Gray. So, we can interpret that Pope and Wordsworth had

much higher rate of recycling words than Burns and Gray. Also, Pope was found to have

recycled words as a greater degree than Wordsworth did. Therefore, it is kind of difficult to

approve Wordsworth’s claim of practicing ‘simpler’ language at least in comparison to Pope.

Extracting and ranking Word-usage means

Figure 12 plots the mean word frequencies of each of the individual poems against their lengths;

this was done to see the effect of the length of a poem on the mean word frequency values (i.e.

rate of word recycling) for the poets.

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Fig. 12. Relationship between mean word frequency and poem length (shorter to longer

from left to right)

Results, for all poets, reveal that as the length of the poems increased, the mean word frequency

value also increased, indicating to a positive correlation between them. And clearly, Wordsworth

was found to have recycled words to the highest degree as the poems grew longer, which is

vindicated by the steep rising slope. Interestingly, Pope also follows the same trend which is

much closer to Wordsworth, and much different from Burns and Gray.

Lexical diversity

Study lexical diversity in a text has its basis in studying hapax legomena, or simply hapax, which

can reveal information about linguistic complexity of a given text (Jockers 71). Basically hapax

refers to the words which occur only ‘once’; these words have often been termed as ‘oncers’

(Davis 33-118), ‘singletons’, or ‘one-zies’ (Jockers 71). The idea here is to study the extent of

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the occurrence of the infrequent words in a text. It is also commonly assumed that the more a

writer uses ‘hapax’, the more complex the language becomes (Jockers 71).

For comparing the percentage of hapax in each of the poets, the Hapax-Token Ration

(HTR) was calculated for each poet; this was done by simply dividing the number of hapax by

the NTT and then by multiplying by 100.

Fig. 13 presents the results of the comparison of the mean HTR across the poets’ works.

It reveals that Wordsworth and Pope had a pretty low percentage of hapax use in relation to

Burns and Gray. Interestingly Pope apparently had the lowest rate of hapax use, even below

Wordsworth.

Fig. 13. Mean hapax-token ratio for all poets

However, since the overall mean can sometimes mislead us with measures that are not

consistently applicable to the different parts of the corpus, we also plotted the HTR of each of the

poems to reveal the distribution of HTR values across individual poems of each poet (see fig.

14). We can make, at least, two assumptions from these distributions: (1) there is a strong

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negative correlation between the length of the poems and the ratio of hapax, and (2) Pope and

Wordsworth has a similar type of trend in contrast to the other two poets. Also, the HTR values

for Pope and Wordsworth seem to have similar range as they descend from the highest to the

lowest (the highest values for them were close to 65-70, the lowest values were between 15 and

20, and they had a pretty similar slope).

Fig. 14. Hapax-token ratio for all poems for individual poets (from left to right, poems are

shorter to longer)

To verify the first assumption, test of correlation was performed for each of the poets,

and strong negative correlation was found (Wordsworth -0.73; Pope -0.78; Burns -0.65; Gray -

0.86). Now, to verify the second assumption regarding the differences between the ratio of hapax

use across the poets, test of ‘ANOVA’ was performed. The test of ‘ANOVA’ would check

reliably if the distributions of the HTR values for the mentioned groups (here each of the poets)

are significantly different from one another, in other words, if they are consistently different

from all the others.

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Table 4

Results of ‘ANOVA’

Df Sum Sq Mean Sq F value P-value

author 3 2639 879.8 6.606 0.000289 ***

Residuals 187 24905 133.2

The output of the ‘ANOVA’ (see table 4) produced a p-value of 0.000289

(conventionally any p-value below 0.05 is considered to be accepted as significant), which

strongly confirmed that the differences between the poets is highly significant, and no one was

likely to have the similar distribution of HTR values like the others. Therefore, Pope was found

to have significantly less ratio of hapax use in his works than any other poets here. And, this

indicates that Wordsworth was not significantly different from Pope in terms of lexical diversity.

CONCLUSION

Though Wordsworth’s WV seemed to be considerably different from the other poets on the first

look of the WVs of all the poets (table 2), he did not seem to be remarkably different in the use

of the vocabularies which might contribute to turn his language to be the least complex. All of

the poets had a few number of words which were used highly (fig. 1 to 4). However, for

Wordsworth the top-frequent words appeared more frequently in contrast to the others (fig. 5). In

the case of the relationship between NTT and NWT, Wordsworth was very similar to Pope,

though considerably different from Burns and Gray. TTR measures also indicated that though

Wordsworth’s was less complex than Burns and Gray, Pope was even lesser than him. Same

findings came from mean word frequency measures, which meant that pope, on average, had a

greater rate of recycling vocabularies. Also, Pope superseded Wordsworth in using lesser extent

of hapax.

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However, Wordsworth had a very high pace of introducing new words to the readers; he

introduced nearly 46% of his words in the first quarter of the corpus. Also, Wordsworth (along

with Burns) maintained a balanced distribution of words from their WVs throughout their

corpus.

Overall, the quantitative measure of this study indicates that Wordsworth’s language was

certainly less complex than that of Burns and Gray; but, it was not essentially ‘simpler’ than

Pope. If readers really feel that Wordsworth has a less complex language than Pope, this might

be due to Wordsworth’s high rate of recycling a small set of words (as indicated by the higher

range of relative frequency measures of the words at the top). We also should consider that the

publication of Lyrical Ballads came out after 54 years of Pope’s death; languages change as a

natural course of time, and so Pope’s language could have seemed to be a bit different in the

context of Wordsworth’s period.

It is striking that Wordsworth’s poetic language had a lot of similarity with that of Pope,

while Wordsworth was much vocal against the conventions of Pope. Griffin’s idea of ‘ghostly

presence of Pope’s texts in Wordsworth’ seems to be a reality here. In Griffin’s words, “the

closest attention is indeed given to those words which, by the process of repetition and tautology,

had come to ear in it a weight, a power, greater than they usually carry. (47)” May be,

Wordsworth was claiming his language to be different from Pope only to undermine the then

Pope’s popularity and pave the way for his own works.

Finally, we need to keep in mind that linguistic complexity is hard to measure outright in

any straightforward means; offering distinctions in binary terms like ‘difficult’/ ‘not difficult’ is

hardly of help. Rather the level of complexity derives from a number of factors related to the use

of linguistic vocabularies, which refer to a ‘continuum’ of the degree of complexity. Also, some

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specific piece of writing by a poet might have more linguistic complexity, while many others

might have less. Therefore, it is often inappropriate to confer a ‘generalized notion’ of

complexity to all the writings of a writer.

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Appendix

List of Poems in the Corpus

Wordsworth 1 Expostulation and Reply

2 The Tables turned; an Evening Scene, on the same subject

3 Animal Tranquillity and Decay, a Sketch

4 The Complaint of a forsaken Indian Woman

5 The Last of the Flock

6 Lines left upon a Seat in a Yew-tree which stands near the Lake of

Esthwaite

7 Goody Blake and Harry Gill

8 The Thorn

9 We are Seven

10 Anecdote for Fathers

11 Lines written at a small distance from my House and sent me by my

little Boy to the Person to whom they are addressed

12 The Female Vagrant

13 Simon Lee, the old Huntsman

14 Lines written in early Spring

15 Lines written when sailing in a Boat at Evening

16 Lines written near Richmond, upon the Thames

17 The Idiot Boy

18 The Mad Mother

19 Lines written above Tintern Abbey

20 Hart-leap Well

21 There was a Boy, &c

22 The Brothers, a Pastoral Poem

23 Ellen Irwin, or the Braes of Kirtle

24 Strange fits of passion I have known, &c.

25 Song

26 A slumber did my spirit seal, &c

27 The Waterfall and the Eglantine

28 The Oak and the Broom, a Pastoral

29 Lucy Gray

30 The Idle Shepherd-Boys or Dungeon-Gill Force, a Pastoral

31 'Tis said that some have died for love, &c.

32 Poor Susan

33 Inscription for the Spot where the Hermitage stood on St. Herbert's

Island, Derwent-Water

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34 Inscription for the House (an Out-house) on the Island at Grasmere

35 To a Sexton

36 Andrew Jones

37 The two Thieves, or the last stage of Avarice

38 A whirl-blast from behind the Hill, &c.

39 Song for the wandering Jew

40 Ruth

41 Lines written with a Slate-Pencil upon a Stone, &c.

42 Lines written on a Tablet in a School

43 The two April Mornings

44 The Fountain, a conversation

45 Nutting

46 Three years she grew in sun and shower, &c.

47 The Pet-Lamb, a Pastoral

48 Written in Germany on one of the coldest days of the century

49 The Childless Father

50 The Old Cumberland Beggar, a Description

51 Rural Architecture

52 A Poet's Epitaph

53 A Character

54 A Fragment

55 Poems on the Naming of Places,

56 Michael, a Pastoral

Pope 1. Spring_The First Pastoral, Or Damon.

2. Summer, The Second Pastoral, Or Alexis.

3. Autumn, The Third Pastoral, Or Hylas And Ægon.

4. Winter, The Fourth Pastoral, Or Daphne.

5. Messiah, A Sacred Eclogue.

6. An Essay On Criticism.

7. The Rape Of The Lock, An Heroi-Comical.

8. Windsor-Forest.

9. Ode On St Cecilia's Day.

10. Two Choruses To The Tragedy Of Brutus.

11. To The Author Of Entitled Successio.

12. Ode On Solitude.

13. The Dying Christian To His Soul.

14. Elegy To The Memory Of An Unfortunate Lady.

15. Prologue To Mr Addison's Tragedy Of Cato.

16. Imitations Of English Poets.

17. The Temple Of Fame.

18. Eloisa To Abelard.

19. Epistle To Robert Earl Of Oxford And Earl Mortimer.

20. Epistle To James Craggs, Esq.

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21. Epistle To Mr Jervas.

22. Epistle To Miss Blount.

23. Epistle To Mrs Teresa Blount.

24. To Mrs M_B_On Her Birthday.

25. To Mr Thomas Southern On His Birthday, 1742.

26. To Mr John Moore, Author Of The Celebrated Worm-Powder.

27. To Mr C, St James's Place.

28. Epitaphs.

29. An Essay On Man.

30. Epistle To Dr Arbuthnot, Or, Prologue To The Satires.

31. Satires And Epistles Of Horace Imitated.

32. The First Epistle Of The First Book Of Horace.

33. The Sixth Epistle Of The First Book Of Horace.

34. The First Epistle Of The Second Book Of Horace.

35. The Second Epistle Of The Second Book Of Horace.

36. Part Of The Ninth Ode Of The Fourth Book.

37. The Satires Of Dr John Donne, Dean Of St Paul's, 171 Versified.

38. Epilogue 177 To The Satires, In Two Dialogues.

Burns 1: Tragic Fragment.

2. The Tarbolton Lasses.

3. Ah, Woe Is Me, My Mother Dear.

4. The Ploughman's Life.

5. The Ronalds Of The Bennals.

6. Winter: A Dirge.

7. Prayer, Under The Pressure Of Violent Anguish.

8. Paraphrase Of The First Psalm.

9. The First Six Verses Of The Ninetieth Psalm Versified.

10. Prayer, In The Prospect Of Death.

11. Stanzas, On The Same Occasion.

12. Fickle Fortune: A Fragment.

13. John Barleycorn: A Ballad.

14. Death And Dying Words Of Poor Mailie.

15. Poor Mailie's Elegy.

16. Remorse: A Fragment.

17. Ballad On The American War.

18. Epistle To John Rankine.

19. A Poet's Welcome To His Love-Begotten Daughter.

20. Man Was Made To Mourn: A Dirge.

21. The Twa Herds; Or, The Holy Tulyie.

22. Epistle To Davie, A Brother Poet.

23. Holy Willie's Prayer.

24. Epitaph On Holy Willie.

25. Death and Doctor Hornbook, A True Story.

26. Epistle To J. Lapraik, An Old Scottish Bard.

27. Second Epistle To J Lapraik.

28. Epistle To William Simson, Schoolmaster.

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29. Elegy On The Death Of Robert Ruisseaux.

30. Epistle To John Goldie, In Kilmarnock.

31. The Holy Fair.

32. Third Epistle To J Lapraik.

33. Epistle To The Rev John M'math.

34. Second Epistle to Davie, A Brother Poet.

35. Halloween.

36. To A Mouse.

37. Adam Armour's Prayer.

38. The Cotter's Saturday Night.

39. Address To The Deil.

40. Scotch Drink.

41. The Auld Farmer's New-Year-Morning Salutation To His Auld

Mare.

42. The Twa Dogs, A Tale.

43. The Author's Earnest Cry And Prayer.

44. The Ordination.

45. Epistle To James Smith.

46. The Vision_Duan First.

47. Suppressed Stanza's Of "The Vision".

48. Address To The Unco Guid, Or The Rigidly Righteous.

49. The Inventory.

50. To John Kennedy, Dumfries House.

51. To Mr. M'Adam, Of Craigen-Gillan.

52. To A Louse, On Seeing One On A Lady's Bonnet, At Church.

53. To A Mountain Daisy.

54. To Ruin.

55. The Lament.

56. Despondency: An Ode.

57. To Gavin Hamilton, Esq.

58. Epistle To A Young Friend.

59. Address Of Beelzebub.

60. A Dream_Thoughts,,,Treason.

61. A Dedication_To Gavin Hamilton, Esq.

62. On A Scotch Bard, Gone To The West Indies.

63. A Bard's Epitaph.

64. Stanzas On Naething.

65. Thomson's Edward and Eleanora.

66. Nature's Law.

67. Reply To A Trimming Epistle Received From A Tailor.

68. The Brigs Of Ayr.

69. Prayer--O Thou Dread Power.

70. Address To The Toothache.

71. Lines On Meeting With Lord Daer.

72. Tam Samson's Elegy.

73. Epistle To Major Logan.

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74. A Winter Night.

75. Address To Edinburgh

76. Address To A Haggis.

77. The Bonie Moor-Hen

78. Epitaph For Mr William Michie

79. Address To Wm. Tytler.

80. Burlesque Lament For The Absence Of William Creech, Publisher.

81. Elegy On "Stella".

82. Elegy On The Death Of Sir James Hunter Blair.

83. Verses Written With A Pencil.

84. The Humble Petition Of Bruar Water.

85. On Scaring Some Water-Fowl In Loch-Turit.

86. A Rose-Bud By My Early Walk.

87. Birthday Ode For 31st December, 1787.

88. On The Death Of Robert Dundas.

89. Sylvander To Clarinda.

90. Epistle To Robert Graham.

Gray 1. Elegy Written in A Country Churchyard

2. On The Spring

3. On The Death of A Favourite Cat

4. On A Distant Prospect of Eton College

5. The Progress of Poesy

6. The Bard

7. Hymn to Adversity

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Hodgart, John. “Language Issues in Studying Burns for Revised Higher: Bard tae Waur?”. 26

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Jockers, Matthew. Text Analysis with R: For students of literature. Forthcoming. Web 30 Sep.

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Lyrical Ballads with Other Poems, 1800 Volume I. Project Gutenberg. Web. 03 Nov. 2013.

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Poems and Songs of Robert Burns. Project Gutenberg. Web. 03 Nov. 2013.

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Select Poems by Thomas Gray. Project Gutenberg. Web. 03 Nov. 2013.

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