The research is aimed at the study of the degree of regularity in the relationship between the frequencies of di erent parts of speech in a verse text, in particular between verbs and nouns. The data-base for the analysis includes 20 sonnets of famous Russian poets of the Silver Age of Russian poetry. The results demonstrate regularity in the distribution of parts of speech frequencies. The exponential function provides a good t.
Parts of speech (PoS) are often used in research in the sphere of quantitative linguistics, stylometry and others [Best, 1994; Stamou, 2008]. Analysis of the frequencies of di erent PoS in a text and proportions between them allow to solve important problems in \linguistics of verse" which has been intensively developing in Russia in the 20th century [Gasparov, 2012].
Depending on the peculiarities of individual styles the frequency of PoS vary to some extent, and sometimes rather considerably [Cech, Altmann, 2013]. Nevertheless it is possible to raise a question of the possible limits of variation and if there are any tendencies of keeping certain proportions between PoS, if there is any general regularity in their frequencies common for all the speakers of the same language. In some studies the results obtained demonstrated the existence of certain order in PoS distribution in speech [Andreev, Popescu, Altmann, 2017]. The present research is aimed at exploring the possibility of such general tendencies in the distribution of parts of speech in verse texts written by authors, di ering in style and creativity manner.
Konstantin Balmont
Maksimilyan Voloshin T1 T2 T3 T4 T5 T6 T7 T8 T9 T11 T12 T13 T14 T15 T16 T17 T18 T19 T20 Vyacheslav Ivanov
Verse is characterized by a much bigger number of restrictions and rules in choosing words than prose whereas sonnets is a poetic genre with one of the most formalized structure and a big number of strict schemes.
Ivanov and M. Voloshin, written by these poets in the rst part of their creative activities. All these poets belong to the period known as the Silver Age of Russian poetry (the beginning of the 20th century) when much attention was paid exactly to this strictly structured genre of sonnet. Below the names (titles) of these sonnets are given with their text numbers in the data-base.
Valery Brusov \Starinnym zolotom i zhelchyu napital. . . " \Zdes' byl svyaschenny les. Bozhestvenny gonets. . . " \Ravnina vod kolishitsa shiroko. . . " \Nad zibkoy ryab'u vod vsayet iz glubiny. . . " \Mare internum"
The following parts of speech were counted in the sonnets: nouns ( N ), adjectives ( A ), verbs ( V ), adverbs (ADV), personal pronouns (PRNP), other types of pronouns which can be used in attributive function (PRNA), participles (PTL), adjectivized participles (PTLA), category of state words { adjectives, used as predicates in non personal sentences (STW).
frequencies. Thus in the sonnet Zhenshchine by Brusov (3) the following numbers of PoS were obtained: 27 nouns, 15 personal pronouns, 9 verbs, 5 adjectives, 4 adjectivized participles, 3 participles and 2 adverbs. (Category of state words and pronouns-adjectives were not registered).
The frequencies of all morphological classes in the samples were ranked in decreasing order so that the most frequent PoS is ranked higher than all the others, the second frequency PoS receives Rank 2, etc. To t the distribution of such ranked PoS frequencies the formula of the exponential function which was suggested for such purposes in [Andreev, Mistecky, Altmann, 2018] was used:
y = a exp( b x) ; where a and b are parameters.
Consider, for example, the above-mentioned sonnet (3). PoS counting in it brought about the following numbers, represented in Table 1. The rst column of this table shows rank numbers, the second represents the PoS classes, the third is their observed frequencies in the sample, the forth column shows theoretically expected frequencies which should be according to the formula. Besides, at the bottom of the table the values of a and b parameters and of the determination coe cient R2 are presented. The coe cient of determination is a measure of goodness of t and provides information on whether a statistical model tted to empirical data is successful. R2 ranges between 0 and 1. When R2 > 0:8 the model ts well.
demonstrated graphically.
value for tting the distribu-tion of PoS in 4 (R2 = 0:8897) and in 7 (R2 = 0:8924) should be considered as a proof of a good t. Since the sonnets were written by di erent poets whose style and manner of writing as well as the topics were di erent, it should be recognized that the distribution of PoS does not depend on such individual matters, but displays some kind of regularity.
into two classes. One of these classes actualizes a static vision of the poetic world [Naumann, Popescu, Altmann, 2012]. In this case the author depicts the world attributing to the themes, expressed by nouns, some features which are viewed as more or less permanent qualities. This is achieved by using such PoS as A , PRNA, PTLA, STW. The other class, on the contrary, gives a description which can be called dynamic, because the features ascribed to the themes in the sonnet are represented as a process or action. This class includes V and PTL. Further on we shall analyze how these two classes of PoS interrelate with one another [Martynenko, 2004].
Replacing the PoS of two classes by the name of the class to which they belong: S for the static description and D for the dynamic one, and omitting all other PoS, one obtains sequences which characterize the level of homogeneity of description.
Let us consider, as example, T3 again. After marking up the two above-mentioned classes we get the following sequence:
D
D
S
S
S
S
S
D
D
D
D
D
S
D
S
S
D
S
D
D
D; This sequence consists of a number of strings formed by repeated elements which further on will be called \runs" [Andreev, Mistecky, Altmann, 2018, p. 50{52]. Here the following runs can be singled out: Little number of runs, including big chains of similar members, indicates intensi ed monotony of description, big number of runs with few elements in them, on the contrary, suggests something like variability in depicting poetic world. In this example the total number of elements in all the runs equals 21, the number of runs equels 9. Thus it follows that the index of the homogeneity of description is Itotal = 21=9 = 2:33. Measuring homogeneity of static and dynamic descriptions separately we get the following: (1) static Ic = 2; 25(9=4); (2) dynamic Iv = 2; 4(12=5). of variability. It should be noted that sonnets are rather brief limited to 14 lines, and nevertheless in a number of cases the di erences are apparent. This can be shown graphically. In Figure 2 the scatterplot demonstrates the relations of two indices| Ic and Iv in 20 sonnets. On the horizontal axis the values of Ic are set, the y-axis sets the values of Iv in the sonnets. 4
The scatterplot shows that priority should be given to y-axis coordinate. X-axis does not provide a basis for classi cation, except for 1 outlier (T20) all the other texts form a rather dense group. On the other hand, index Iv , showing the dynamic homogeneity, divides the sonnets into 2 groups. The rst one consists of 2, 3, 5, 9 17. It should be noted that 2 and 9 completely overlap and are marked by a common dot. All the other sonnets form another group. At the level of Iv = 1:5 it is split into two subgroups of equal number of texts. The homogeneity index of dynamics in description Iv = 1:5 is observed in three texts (15, 18, 20) thus forming a basis for the splitting of the whole group. Above and below this borderline there are 6 texts in each subgroup.
On the whole it is possible to conclude that this research demonstrated some order in all PoS distribution in sonnets and the relations between words which depict static and dynamic description of the poetic world.