Skogen och sjön - Berättelser by Gustaf af Geijerstam : Difficulty Assessment for Swedish Learners

How difficult is Skogen och sjön - Berättelser for Swedish learners? We have performed multiple tests on its full text (freely available here) of approximately 64,473, crunched all the numbers for you and present the results below.

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Difficulty Assessment Summary

We have estimated Skogen och sjön - Berättelser to have a difficulty score of 48. Here're its scores:

Measure Score
easy difficult (1 - 100)
Overall Difficulty 48% 48
Vocabulary Difficulty 58% 58
Grammatical Difficulty 39% 39

Vocabulary Difficulty: Breakdown

58%

Vocabulary difficulty: 58%

This score has been calculated based on frequency vocabulary (the top most frequently used words in Swedish). It combines various measures of Skogen och sjön - Berättelser'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 Skogen och sjön - Berättelser:

Vocabulary difficulty breakdown for Skogen och sjön  - Berättelser: a test for Swedish top frequency vocabulary

We have also calculated the following approximate data on the vocabulary in Skogen och sjön - Berättelser:

Measure Score
Measure Score
Number of words 64,473
Number of unique words 7,410
Number of recognized words for names/places/other entities 2,747
Number of very rare non-entity words 1,844
Number of sentences 9,999
Average number of words/sentence 6

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 7,261 words (where all the forms of the word are still counted as unique words) in Swedish to be able to read Skogen och sjön - Berättelser without a dictionary and fully understand it.

Grammatical Difficulty: Breakdown

39%

Grammatical difficulty: 39%

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 5
Type/Token Ratio (TTR) 0.114932
Root type/Token Ratio (RTTR) 0.00000178264
Corrected type/Token Ratio (CTTR) 0.000000891318
MTLD Index 50
HDD Index 57
Yule's I Index 56
Lexical Diversity Index (MTLD + HD-D + Yule's I) 54

The type-token ratio (TTR) of Skogen och sjön - Berättelser is 0.114932. 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 7,410, while the number of words is 64,473, so the TTR is 7,410 / 64,473 = 0.114932. 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, 7,410 / (64,473 * 64,473) = 0.00000178264), while in CTTR, it is divided by a square of the number of words, multiplied twice 7,410 / 2 * (64,473 * 64,473) = 0.000000891318). 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 54 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 39.

Other Information about Skogen och sjön - Berättelser by Gustaf af Geijerstam

We provide you a sample of the text below, however, the full text of the Skogen och sjön - Berättelser is also available free of charge on our website.

Sample of text:

Han såg upp mot Norman, och hans ansiktsuttryck var alldeles tomt. Det var, som om hans själ varit borta. — Det kom så naturligt alltihop, sade han. Men sedan Sammel yttrat detta, tyckte han, att han gjort nog. Och Norman var icke i stånd att få ett ord mer ur honom. Det blef tråkigt att sitta däruppe i sällskap med en, som bara teg och envist stirrade ut i blåsten. Därför gick Norman om en stund, och Sammel såg hans breda rygg försvinna, där stållinan svängde kring klippan. Då reste han sig och sparkade upp dörren på vid gafvel, så att isvinden fick blåsa in. Där stod han i kölden och brann som i feber. ...

Top most frequently used words in Skogen och sjön - Berättelser by Gustaf af Geijerstam*

Position Word Repetitions Part of all words
Position Word Repetitions Part of all words
1 och 3,088 4.79%
2 han 2,011 3.12%
3 att 1,584 2.46%
4 som 1,281 1.99%
5 det 1,211 1.88%
6 var 890 1.38%
7 hon 878 1.36%
8 867 1.34%
9 sig 759 1.18%
10 en 682 1.06%
11 den 622 0.96%
12 614 0.95%
13 hade 588 0.91%
14 med 584 0.91%
15 för 584 0.91%
16 till 555 0.86%
17 honom 506 0.78%
18 inte 487 0.76%
19 om 477 0.74%
20 Men 401 0.62%
21 när 389 0.6%
22 de 360 0.56%
23 icke 355 0.55%
24 gick 344 0.53%
25 skulle 342 0.53%
26 kunde 323 0.5%
27 af 320 0.5%
28 kom 315 0.49%
29 Johan 299 0.46%
30 jag 290 0.45%
31 Anders 290 0.45%
32 Sammel 285 0.44%
33 henne 279 0.43%
34 hans 269 0.42%
35 blef 253 0.39%
36 aldrig 249 0.39%
37 är 247 0.38%
38 öfver 244 0.38%
39 där 242 0.38%
40 233 0.36%
41 såg 230 0.36%
42 nu 230 0.36%
43 ett 220 0.34%
44 du 207 0.32%
45 hvad 205 0.32%
46 sade 202 0.31%
47 sin 200 0.31%
48 själf 195 0.3%
49 än 189 0.29%
50 allt 185 0.29%
51 har 182 0.28%
52 ut 179 0.28%
53 något 172 0.27%
54 ville 172 0.27%
55 Ty 168 0.26%
56 157 0.24%
57 Kristin 151 0.23%
58 dem 151 0.23%
59 sitt 150 0.23%
60 från 150 0.23%
61 vid 150 0.23%
62 upp 148 0.23%
63 ingen 148 0.23%
64 också 148 0.23%
65 fram 147 0.23%
66 fick 146 0.23%
67 satt 143 0.22%
68 Elsa 139 0.22%
69 gång 139 0.22%
70 detta 138 0.21%
71 efter 137 0.21%
72 in 136 0.21%
73 varit 136 0.21%
74 hennes 135 0.21%
75 134 0.21%
76 man 130 0.2%
77 hur 125 0.19%
78 mig 123 0.19%
79 visste 123 0.19%
80 Per 121 0.19%
81 sina 118 0.18%
82 utan 117 0.18%
83 tänkte 115 0.18%
84 eller 113 0.18%
85 kan 112 0.17%
86 Agust 111 0.17%
87 länge 106 0.16%
88 se 105 0.16%
89 komma 104 0.16%
90 längre 103 0.16%
91 mycket 102 0.16%
92 därför 102 0.16%
93 ha 100 0.16%
94 fått 100 0.16%
95 kände 99 0.15%
96 väl 99 0.15%
97 tog 99 0.15%
98 tyckte 97 0.15%
99 stod 95 0.15%
100 bara 95 0.15%
101 vara 93 0.14%
102 åt 92 0.14%
103 skogen 91 0.14%
104 gjorde 91 0.14%
105 Håkan 91 0.14%
106 låg 90 0.14%
107 omkring 90 0.14%
108 säga 89 0.14%
109 moster 87 0.13%
110 alla 87 0.13%
111 Petter 85 0.13%
112 under 85 0.13%
113 mot 84 0.13%
114 någon 83 0.13%
115 alltid 82 0.13%
116 hvilken 82 0.13%
117 ej 81 0.13%
118 hela 81 0.13%
119 ingenting 79 0.12%
120 igen 79 0.12%
121 heller 78 0.12%
122 här 78 0.12%
123 dig 78 0.12%
124 bort 77 0.12%
125 ord 76 0.12%
126 andra 76 0.12%
127 hem 75 0.12%
128 nog 75 0.12%
129 göra 74 0.11%
130 annat 73 0.11%
131 dag 72 0.11%
132 hörde 72 0.11%
133 ska 71 0.11%
134 ur 71 0.11%
135 mer 71 0.11%
136 sist 70 0.11%
137 ned 70 0.11%
138 gjort 69 0.11%
139 båda 69 0.11%
140 ändå 66 0.1%
141 många 65 0.1%
142 vill 64 0.1%
143 ensam 64 0.1%
144 förr 64 0.1%
145 kommit 64 0.1%
146 hvar 63 0.1%
147 gamla 63 0.1%
148 lif 61 0.09%
149 denna 61 0.09%
150 Janne 61 0.09%
151 tid 60 0.09%
152 långt 60 0.09%
153 hustrun 60 0.09%
154 hustru 57 0.09%
155 tala 56 0.09%
156 barn 56 0.09%
157 kommer 56 0.09%
158 blifvit 56 0.09%
159 mannen 56 0.09%
160 allting 55 0.09%
161 fanns 55 0.09%
162 inom 54 0.08%
163 ifrån 54 0.08%
164 ögon 54 0.08%
165 får 54 0.08%
166 innan 54 0.08%
167 gått 54 0.08%
168 pengar 53 0.08%
169 svarade 53 0.08%
170 både 53 0.08%
171 genom 53 0.08%
172 bli 52 0.08%
173 tankar 51 0.08%
174 gården 50 0.08%
175 år 50 0.08%
176 ännu 50 0.08%
177 sådant 50 0.08%
178 mera 50 0.08%
179 Bertil 49 0.08%
180 emot 49 0.08%
181 lifvet 48 0.07%
182 två 48 0.07%
183 annan 48 0.07%

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 Skogen och sjön  - Berättelser by Gustaf af Geijerstam

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.