Literature analysis for language learners: Furstinnan Gogol. Skådespel i fem akter by Harald Molander

Furstinnan Gogol. Skådespel i fem akter by Harald Molander : Difficulty Assessment for Swedish Learners

How difficult is Furstinnan Gogol. Skådespel i fem akter for Swedish learners? We have performed multiple tests on its full text (freely available here) of approximately 25,119, crunched all the numbers for you and present the results below.

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Difficulty Assessment Summary

We have estimated Furstinnan Gogol. Skådespel i fem akter to have a difficulty score of 53. Here're its scores:

Measure Score
easy difficult (1 - 100)
Overall Difficulty 53% 53
Vocabulary Difficulty 66% 66
Grammatical Difficulty 40% 40

Vocabulary Difficulty: Breakdown

66%

Vocabulary difficulty: 66%

This score has been calculated based on frequency vocabulary (the top most frequently used words in Swedish). It combines various measures of Furstinnan Gogol. Skådespel i fem akter's text analyzed in terms of frequency vocabulary: a plain vocabulary score, frequency-weighted vocabulary score, banded frequency vocabulary scores based on vocabulary of the text falling in the top 1,000 or 2,000 most frequent words, etc. Here's a further breakdown of how often the top most frequently used words in Swedish appear in the full text of Furstinnan Gogol. Skådespel i fem akter:

Vocabulary difficulty breakdown for Furstinnan Gogol. Skådespel i fem akter: a test for Swedish top frequency vocabulary

We have also calculated the following approximate data on the vocabulary in Furstinnan Gogol. Skådespel i fem akter:

Measure Score
Measure Score
Number of words 25,119
Number of unique words 4,079
Number of recognized words for names/places/other entities 2,090
Number of very rare non-entity words 1,044
Number of sentences 6,108
Average number of words/sentence 4

There is some research suggesting that that you need to know about 98% of a text's vocabulary in order to be able to infer the meaning of unknown words when reading. If true, this means that you would need to know around 3,997 words (where all the forms of the word are still counted as unique words) in Swedish to be able to read Furstinnan Gogol. Skådespel i fem akter without a dictionary and fully understand it.

Grammatical Difficulty: Breakdown

40%

Grammatical difficulty: 40%

Here is the further grammatical comparison on this text. You can find an explanation of all these scores below.

Measure Score
Measure Score
Automated Readability Index 2
Coleman-Liau Index 4
Type/Token Ratio (TTR) 0.162387
Root type/Token Ratio (RTTR) 0.00000646471
Corrected type/Token Ratio (CTTR) 0.00000323235
MTLD Index 44
HDD Index 61
Yule's I Index 66
Lexical Diversity Index (MTLD + HD-D + Yule's I) 57

The type-token ratio (TTR) of Furstinnan Gogol. Skådespel i fem akter is 0.162387. The TTR is the most basic measure of lexical diversity. To calculate it, we divide the number of unique words by the number of words in the text. For example, for this text, the number of unique words is 4,079, while the number of words is 25,119, so the TTR is 4,079 / 25,119 = 0.162387. However, the TTR is a very crude measure, as it is extremely dependent on text length. The longer the text, the lower the TTR is usually going to be, since common words tend to often repeat. Especially since the number of words in this text is more than 1,000, the TTR is not likely to give an accurate measure.

The root type-token ratio (RTTR) and corrected type-token ratio (CTTR) are measures which were suggested by researchers to partially address the problem of TTR's variance on text length. In the RTTR, the number of unique words is divided by a square of the number of words (therefore, 4,079 / (25,119 * 25,119) = 0.00000646471), while in CTTR, it is divided by a square of the number of words, multiplied twice 4,079 / 2 * (25,119 * 25,119) = 0.00000323235). However, these measures are not as easily readable, and also there is a growing body of research asserting that CTTR and RTTR do not effectively address the problems of text length. Therefore, while we do provide the full text's TTR, RTTR and CTTR on this page, these fiqures do not form part of our final calculations.

The Automated Readability Index (ARI) is one readability measure that has been developed by researchers over the years. The formula for calculating the ARI is as follows:
Formula for calculating the Automated Readability Index

The ARI should compute a reading level approximately corresponding to the reader's grade level (assuming the reader undertakes formal education). Thus, for example, a value of 1 is kindergarten level, while a value of 12 or 13 is the last year of school, and 14 is a sophomore at college. The current ARI of this text is 2, making it understandable for 2-grade students at their expected level of education.

The Coleman Liau Index (CLI) is a similar index designed by Meri Coleman and T. L. Liau, and it is supposed to compute the grade level of the reader (thus, for example, sophomore level material would be around grade 14, or year 14 of formal education, while kindergarten / primary school level material would be close to grade 1 in the CLI). The CLI is usually slightly higher than the ARI. The CLI is computed with this formula:
Formula for calculating the Coleman-Liau Readability Index

It is notable that other indexes exist, such as the Flesch-Kincaid Reading Ease, Gunning-Fog Score, and others, but we have chosen not to include them, since, contrary to the ARI and CLI, such other indexes are based on a syllable count and therefore arguably only work for English and not Swedish.

We compute a further compound lexical diversity index, which should range from 1 to a 100 (with the standard deviation being around 10, and its average value being around 50) - it is 57 in the present case. The compound lexical diversity index consists of the following indexes, averaged out (and also provided in the table above):

  • the Measure of Textual Lexical Diversity (MTLD) index - a measure which is based on computing the TTR for increasingly larger parts of the text until the TTR drops below a certain threshold point (around 0.7 in our case) - in which case, the TTR is reset, and the overall counter is increased; the counter is at the end divided by the number of words in text; as a result, the MTLD does not significantly vary by text length;
  • the Yule's I index (based on Yule's K characteristic inverted) - an index based on the work of the statistician G.U. Yule, who published his index of Frequency Vocabulary in his paper "The statistical study of literary vocabulary"; Yule's I takes into account the number of words in the text, and a compound summed measure of word frequency;
  • the Hypergeometric Distribution D (HD-D) index (based on vocd) - an index which assesses the contribution of each word to the diversity of the text; to calculate such contributions, a hypergeometric distribution is used to compute probabilities of each word appearing in word samples extracted from the text; then such distributions are divided by sample sizes and added up;

Our overall measure of grammatical diversity is based on a combination of the compound lexical diversity index (which includes the MTLD, Yule's I and HD-D indexes), the ARI and CLI, all normalized and given certain weight. The score should normally range from 1 to 100. In this case, the score is 40.

Other Information about Furstinnan Gogol. Skådespel i fem akter by Harald Molander

We provide you a sample of the text below, however, the full text of the Furstinnan Gogol. Skådespel i fem akter is also available free of charge on our website.

Sample of text:

Det blir strax tusen verst längre. DITMAR. N’importe ! BARONESSAN. Hvad ni är rolig! NADJESHDA. Voilà qui est drôle! BARONESSAN. Mais c’est chic ... SHIVOJSKIJ. Chez nous ... en Russie . . . DITMAR. Följer ni med, Dmitrij? SHIVOJSKIJ. Tack, den der färden synes mig väl vågad . . . DITMAR. Ni har inte något hjerta, Dmitrij — eller också sitter det i halsgropen på er. SHIVOJSKIJ. ...

Top most frequently used words in Furstinnan Gogol. Skådespel i fem akter by Harald Molander*

Position Word Repetitions Part of all words
Position Word Repetitions Part of all words
1 och 524 2.09%
2 är 503 2%
3 att 462 1.84%
4 det 457 1.82%
5 ni 426 1.7%
6 jag 423 1.68%
7 inte 396 1.58%
8 NATALIJA 384 1.53%
9 DMITRIJEV 288 1.15%
10 som 283 1.13%
11 på 277 1.1%
12 mig 277 1.1%
13 till 261 1.04%
14 er 217 0.86%
15 för 208 0.83%
16 en 203 0.81%
17 har 194 0.77%
18 du 193 0.77%
19 med 167 0.66%
20 ROMILOV 159 0.63%
21 om 157 0.63%
22 TATIJANA 149 0.59%
23 var 137 0.55%
24 så 136 0.54%
25 henne 136 0.54%
26 honom 129 0.51%
27 hon 123 0.49%
28 SONJA 114 0.45%
29 Ja 112 0.45%
30 går 108 0.43%
31 sig 105 0.42%
32 han 104 0.41%
33 ett 101 0.4%
34 min 100 0.4%
35 skall 100 0.4%
36 dig 100 0.4%
37 den 98 0.39%
38 här 92 0.37%
39 NADJESHDA 91 0.36%
40 kan 86 0.34%
41 upp 86 0.34%
42 vill 84 0.33%
43 de 84 0.33%
44 ser 81 0.32%
45 men 80 0.32%
46 Hvad 79 0.31%
47 ZOTOV 77 0.31%
48 Boris 75 0.3%
49 FOLENKO 74 0.29%
50 då 72 0.29%
51 nu 69 0.27%
52 der 69 0.27%
53 ju 68 0.27%
54 ha 67 0.27%
55 af 67 0.27%
56 något 67 0.27%
57 allt 66 0.26%
58 från 65 0.26%
59 än 65 0.26%
60 vet 65 0.26%
61 man 65 0.26%
62 när 61 0.24%
63 Nej 59 0.23%
64 gå 57 0.23%
65 kommer 56 0.22%
66 sjelf 55 0.22%
67 skulle 55 0.22%
68 vi 54 0.21%
69 dem 54 0.21%
70 tror 54 0.21%
71 SCENEN 54 0.21%
72 ut 53 0.21%
73 mycket 49 0.2%
74 ned 49 0.2%
75 öfver 48 0.19%
76 vid 48 0.19%
77 efter 47 0.19%
78 komma 47 0.19%
79 någon 47 0.19%
80 GENERALEN 46 0.18%
81 åt 46 0.18%
82 ingen 44 0.18%
83 hans 43 0.17%
84 fonden 42 0.17%
85 tillbaka 42 0.17%
86 varit 41 0.16%
87 far 41 0.16%
88 se 41 0.16%
89 aldrig 41 0.16%
90 vara 41 0.16%
91 hade 40 0.16%
92 Hvem 39 0.16%
93 också 37 0.15%
94 alla 36 0.14%
95 Ivanovitsch 35 0.14%
96 BARONESSAN 35 0.14%
97 mot 35 0.14%
98 gör 33 0.13%
99 SHIVOJSKIJ 33 0.13%
100 Ah 33 0.13%
101 venster 32 0.13%
102 hit 32 0.13%
103 oss 31 0.12%
104 blott 31 0.12%
105 får 30 0.12%
106 dag 30 0.12%
107 tro 29 0.12%
108 Hvarför 28 0.11%
109 ty 28 0.11%
110 häftigt 28 0.11%
111 älskar 28 0.11%
112 derför 28 0.11%
113 väl 27 0.11%
114 höger 27 0.11%
115 visst 27 0.11%
116 excellens 27 0.11%
117 hennes 26 0.1%
118 fönstret 26 0.1%
119 detta 26 0.1%
120 mina 26 0.1%
121 ber 26 0.1%
122 eller 25 0.1%
123 sagt 25 0.1%
124 bli 25 0.1%
125 kunna 25 0.1%
126 måste 25 0.1%
127 utan 25 0.1%
128 under 25 0.1%
129 ville 24 0.1%
130 sade 24 0.1%
131 gång 24 0.1%
132 göra 24 0.1%
133 annat 24 0.1%
134 ingenting 24 0.1%
135 hos 24 0.1%
136 få 24 0.1%
137 dö 24 0.1%
138 säger 24 0.1%
139 DITMAR 24 0.1%
140 mitt 24 0.1%
141 friheten 24 0.1%
142 tala 23 0.09%
143 kanske 23 0.09%
144 säga 23 0.09%
145 andra 22 0.09%
146 sedan 22 0.09%
147 kunde 22 0.09%
148 hela 22 0.09%
149 sin 22 0.09%
150 äro 21 0.08%
151 morgon 21 0.08%
152 blir 21 0.08%
153 Ryssland 21 0.08%
154 står 21 0.08%
155 stiger 21 0.08%
156 sitt 21 0.08%
157 Paus 20 0.08%
158 såg 20 0.08%
159 vilja 20 0.08%
160 förra 20 0.08%
161 kom 20 0.08%
162 afton 20 0.08%
163 Åh 20 0.08%
164 verlden 20 0.08%

This list excludes punctuation or single-letter words, also some different-case repeats of the same words.

If you think the text would be accessible to you, you can read it on our site (click on the cover to access):

Cover of Furstinnan Gogol. Skådespel i fem akter by Harald Molander

Other resources and languages

If you like this analysis, you should have a look at out our lists of Swedish short stories and Swedish books.

If you like literature as a means to learn languages - please take a look at our project Interlinear Books. We even have a Swedish Interlinear book available for purchase.