Marthas barn by Bertha von Suttner : Difficulty Assessment for Swedish Learners

How difficult is Marthas barn for Swedish learners? We have performed multiple tests on its full text (freely available here) of approximately 83,550, crunched all the numbers for you and present the results below.

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Difficulty Assessment Summary

We have estimated Marthas barn to have a difficulty score of 60. Here're its scores:

Measure Score
easy difficult (1 - 100)
Overall Difficulty 60% 60
Vocabulary Difficulty 64% 64
Grammatical Difficulty 57% 57

Vocabulary Difficulty: Breakdown

64%

Vocabulary difficulty: 64%

This score has been calculated based on frequency vocabulary (the top most frequently used words in Swedish). It combines various measures of Marthas barn'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 Marthas barn:

Vocabulary difficulty breakdown for Marthas barn: a test for Swedish top frequency vocabulary

We have also calculated the following approximate data on the vocabulary in Marthas barn:

Measure Score
Measure Score
Number of words 83,550
Number of unique words 11,914
Number of recognized words for names/places/other entities 3,519
Number of very rare non-entity words 3,649
Number of sentences 11,926
Average number of words/sentence 7

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 11,675 words (where all the forms of the word are still counted as unique words) in Swedish to be able to read Marthas barn without a dictionary and fully understand it.

Grammatical Difficulty: Breakdown

57%

Grammatical difficulty: 57%

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 4
Coleman-Liau Index 8
Type/Token Ratio (TTR) 0.142597
Root type/Token Ratio (RTTR) 0.00000170673
Corrected type/Token Ratio (CTTR) 0.000000853365
MTLD Index 70
HDD Index 69
Yule's I Index 86
Lexical Diversity Index (MTLD + HD-D + Yule's I) 75

The type-token ratio (TTR) of Marthas barn is 0.142597. 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 11,914, while the number of words is 83,550, so the TTR is 11,914 / 83,550 = 0.142597. 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, 11,914 / (83,550 * 83,550) = 0.00000170673), while in CTTR, it is divided by a square of the number of words, multiplied twice 11,914 / 2 * (83,550 * 83,550) = 0.000000853365). 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 4, making it understandable for 4-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 75 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 57.

Other Information about Marthas barn by Bertha von Suttner

We provide you a sample of the text below, however, the full text of the Marthas barn is also available free of charge on our website.

Sample of text:

Nu skyndade de fyra tärnorna fram till bruden och omfamnade henne häftigt; från alla sidor handtryckningar, kyssar, gratulationer, bugningar . . . Sylvias bäfvan vek för den åter vaknande känslan att veta sig vara den mycket afundade, mycket beundrade hufvudpersonen vid denna lysande, viktiga fest. Och då hon fick se sin vackre fästman, som med glädjestrålande ögon kom emot henne, kände hon en varm våg af lidelsefull lycka genomströmma sitt inre. Efter ytterligare ett par minuters hälsningar och samtal började man att under Rudolfs ledning ordna processionen. För att komma till slottskapellet måste man passera två trappor och en lång korridor. Hela denna väg var mattbelagd och beströdd med grönt och blommor. Man kände en doft, som erinrade om Kristi lekamens fest. Klockklang och ...

Top most frequently used words in Marthas barn by Bertha von Suttner*

Position Word Repetitions Part of all words
Position Word Repetitions Part of all words
1 och 2,044 2.45%
2 att 1,548 1.85%
3 en 1,339 1.6%
4 det 1,124 1.35%
5 som 984 1.18%
6 jag 927 1.11%
7 han 863 1.03%
8 icke 855 1.02%
9 af 852 1.02%
10 till 760 0.91%
11 746 0.89%
12 är 715 0.86%
13 den 709 0.85%
14 sig 702 0.84%
15 för 692 0.83%
16 med 641 0.77%
17 hon 637 0.76%
18 var 590 0.71%
19 584 0.7%
20 ett 515 0.62%
21 de 493 0.59%
22 hade 478 0.57%
23 mig 473 0.57%
24 man 433 0.52%
25 om 402 0.48%
26 har 382 0.46%
27 skulle 348 0.42%
28 du 340 0.41%
29 honom 328 0.39%
30 sin 316 0.38%
31 denna 305 0.37%
32 hans 302 0.36%
33 nu 297 0.36%
34 henne 293 0.35%
35 men 292 0.35%
36 från 274 0.33%
37 270 0.32%
38 ju 267 0.32%
39 Rudolf 257 0.31%
40 Sylvia 249 0.3%
41 ej 247 0.3%
42 min 245 0.29%
43 äfven 244 0.29%
44 detta 242 0.29%
45 endast 236 0.28%
46 hennes 234 0.28%
47 något 228 0.27%
48 måste 210 0.25%
49 ni 208 0.25%
50 dig 203 0.24%
51 alla 185 0.22%
52 kan 180 0.22%
53 dessa 178 0.21%
54 hvilka 177 0.21%
55 er 177 0.21%
56 allt 175 0.21%
57 vid 174 0.21%
58 öfver 173 0.21%
59 än 171 0.2%
60 mycket 169 0.2%
61 eller 162 0.19%
62 vara 155 0.19%
63 ännu 147 0.18%
64 själf 146 0.17%
65 hvilken 145 0.17%
66 andra 145 0.17%
67 kunna 143 0.17%
68 kommer 142 0.17%
69 dem 141 0.17%
70 sitt 136 0.16%
71 genom 135 0.16%
72 vi 133 0.16%
73 gång 131 0.16%
74 när 129 0.15%
75 hur 128 0.15%
76 sina 127 0.15%
77 utan 126 0.15%
78 där 125 0.15%
79 samma 125 0.15%
80 väl 122 0.15%
81 vill 122 0.15%
82 kunde 121 0.14%
83 redan 118 0.14%
84 ord 118 0.14%
85 under 116 0.14%
86 kände 113 0.14%
87 hvad 112 0.13%
88 112 0.13%
89 aldrig 112 0.13%
90 dock 110 0.13%
91 Martha 110 0.13%
92 mitt 109 0.13%
93 skall 109 0.13%
94 ha 109 0.13%
95 bli 108 0.13%
96 åt 108 0.13%
97 vet 106 0.13%
98 sade 105 0.13%
99 mot 104 0.12%
100 åter 104 0.12%
101 mer 104 0.12%
102 ville 103 0.12%
103 efter 101 0.12%
104 upp 101 0.12%
105 oss 99 0.12%
106 sedan 99 0.12%
107 säga 98 0.12%
108 någon 96 0.11%
109 helt 96 0.11%
110 några 93 0.11%
111 Bresser 93 0.11%
112 in 93 0.11%
113 här 87 0.1%
114 varit 84 0.1%
115 mor 83 0.1%
116 äro 83 0.1%
117 söka 83 0.1%
118 Ja 82 0.1%
119 tillbaka 81 0.1%
120 göra 78 0.09%
121 Hugo 78 0.09%
122 också 77 0.09%
123 kärlek 77 0.09%
124 dag 76 0.09%
125 voro 75 0.09%
126 hela 75 0.09%
127 hvarandra 74 0.09%
128 ut 73 0.09%
129 Nej 73 0.09%
130 liksom 72 0.09%
131 din 72 0.09%
132 inre 71 0.08%
133 lycka 68 0.08%
134 gick 68 0.08%
135 två 65 0.08%
136 annat 65 0.08%
137 dess 64 0.08%
138 sätt 64 0.08%
139 vore 64 0.08%
140 sådan 62 0.07%
141 tankar 62 0.07%
142 nog 62 0.07%
143 komma 61 0.07%
144 stod 61 0.07%
145 hvilket 60 0.07%
146 fram 59 0.07%
147 densamma 59 0.07%
148 all 59 0.07%
149 just 58 0.07%
150 ingen 58 0.07%
151 såg 57 0.07%
152 första 57 0.07%
153 kom 57 0.07%
154 år 57 0.07%
155 tid 57 0.07%
156 mest 57 0.07%
157 ned 57 0.07%
158 tala 57 0.07%
159 först 56 0.07%
160 deras 56 0.07%
161 känner 56 0.07%
162 ur 56 0.07%
163 lifvet 56 0.07%
164 låg 56 0.07%
165 Ack 55 0.07%
166 verkligen 55 0.07%
167 mina 55 0.07%
168 stora 54 0.06%
169 detsamma 54 0.06%
170 hos 54 0.06%
171 Cajetane 53 0.06%
172 båda 53 0.06%
173 lif 53 0.06%
174 visste 53 0.06%
175 stor 53 0.06%
176 barn 52 0.06%

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 Marthas barn by Bertha von Suttner

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.