Fata Morgana. En Stockholmsnovell by Henning Berger : Difficulty Assessment for Swedish Learners

How difficult is Fata Morgana. En Stockholmsnovell for Swedish learners? We have performed multiple tests on its full text (freely available here) of approximately 74,916, crunched all the numbers for you and present the results below.

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Difficulty Assessment Summary

We have estimated Fata Morgana. En Stockholmsnovell to have a difficulty score of 64. Here're its scores:

Measure Score
easy difficult (1 - 100)
Overall Difficulty 64% 64
Vocabulary Difficulty 82% 82
Grammatical Difficulty 47% 47

Vocabulary Difficulty: Breakdown

82%

Vocabulary difficulty: 82%

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

Vocabulary difficulty breakdown for Fata Morgana. En Stockholmsnovell: a test for Swedish top frequency vocabulary

We have also calculated the following approximate data on the vocabulary in Fata Morgana. En Stockholmsnovell:

Measure Score
Measure Score
Number of words 74,916
Number of unique words 13,955
Number of recognized words for names/places/other entities 3,172
Number of very rare non-entity words 3,880
Number of sentences 13,186
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 13,675 words (where all the forms of the word are still counted as unique words) in Swedish to be able to read Fata Morgana. En Stockholmsnovell without a dictionary and fully understand it.

Grammatical Difficulty: Breakdown

47%

Grammatical difficulty: 47%

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 7
Type/Token Ratio (TTR) 0.186275
Root type/Token Ratio (RTTR) 0.00000248646
Corrected type/Token Ratio (CTTR) 0.00000124323
MTLD Index 60
HDD Index 60
Yule's I Index 61
Lexical Diversity Index (MTLD + HD-D + Yule's I) 60

The type-token ratio (TTR) of Fata Morgana. En Stockholmsnovell is 0.186275. 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 13,955, while the number of words is 74,916, so the TTR is 13,955 / 74,916 = 0.186275. 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, 13,955 / (74,916 * 74,916) = 0.00000248646), while in CTTR, it is divided by a square of the number of words, multiplied twice 13,955 / 2 * (74,916 * 74,916) = 0.00000124323). 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 60 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 47.

Other Information about Fata Morgana. En Stockholmsnovell by Henning Berger

We provide you a sample of the text below, however, the full text of the Fata Morgana. En Stockholmsnovell is also available free of charge on our website.

Sample of text:

Jag skulle kunna förklara mig själf så att säga i miljöfärger. Ja, ja, nu kommer jag visst på afvägar — Han svängde med käppen och skrattade. — Allt är sig likt, var det ja. Han kikade med hufvudet på sned motDjurgården — baracker, villor, svarta pråmar, svensk flagga här och där, ja, ja... — Och en grön skuta, sade Yrsa. — Och ett svart skrof med röd vattenlinje under Beckholmen... Solen stod i sydväst, klockan var half tre. Söders höga granitvägg liknade, som han alltid tyckt, en klippfästning, och sen kom kranar, kyrktornet och de tre fabriksskorstenarna, tripp, trapp, trull, upp till Fåfängan ...

Top most frequently used words in Fata Morgana. En Stockholmsnovell by Henning Berger*

Position Word Repetitions Part of all words
Position Word Repetitions Part of all words
1 och 3,117 4.16%
2 en 1,539 2.05%
3 han 1,445 1.93%
4 det 1,427 1.9%
5 som 1,197 1.6%
6 1,020 1.36%
7 var 1,003 1.34%
8 att 813 1.09%
9 jag 747 1%
10 med 744 0.99%
11 ett 651 0.87%
12 den 646 0.86%
13 till 558 0.74%
14 är 527 0.7%
15 hade 504 0.67%
16 af 485 0.65%
17 476 0.64%
18 för 474 0.63%
19 sig 459 0.61%
20 de 435 0.58%
21 icke 405 0.54%
22 om 404 0.54%
23 Helge 343 0.46%
24 men 318 0.42%
25 hon 311 0.42%
26 Bendel 292 0.39%
27 inte 286 0.38%
28 du 280 0.37%
29 såg 268 0.36%
30 nu 255 0.34%
31 sade 242 0.32%
32 från 241 0.32%
33 honom 236 0.32%
34 där 227 0.3%
35 har 219 0.29%
36 upp 213 0.28%
37 ut 212 0.28%
38 öfver 210 0.28%
39 vid 207 0.28%
40 198 0.26%
41 skulle 195 0.26%
42 mig 180 0.24%
43 eller 172 0.23%
44 kunde 170 0.23%
45 hans 164 0.22%
46 in 162 0.22%
47 något 162 0.22%
48 ju 152 0.2%
49 kom 150 0.2%
50 också 146 0.19%
51 här 139 0.19%
52 sin 138 0.18%
53 blef 135 0.18%
54 alla 134 0.18%
55 gick 134 0.18%
56 efter 134 0.18%
57 allt 133 0.18%
58 under 132 0.18%
59 mot 131 0.17%
60 stod 125 0.17%
61 hvad 124 0.17%
62 ej 119 0.16%
63 Yrsa 118 0.16%
64 ha 116 0.15%
65 själf 115 0.15%
66 man 114 0.15%
67 gamla 111 0.15%
68 vi 109 0.15%
69 se 108 0.14%
70 ned 108 0.14%
71 denna 106 0.14%
72 mer 105 0.14%
73 än 103 0.14%
74 gång 100 0.13%
75 varit 98 0.13%
76 kan 97 0.13%
77 detta 97 0.13%
78 ni 97 0.13%
79 Ja 96 0.13%
80 vara 96 0.13%
81 kände 96 0.13%
82 Nej 95 0.13%
83 tänkte 94 0.13%
84 sitt 93 0.12%
85 utan 92 0.12%
86 bara 92 0.12%
87 henne 89 0.12%
88 låg 88 0.12%
89 dem 88 0.12%
90 litet 88 0.12%
91 ännu 88 0.12%
92 ville 88 0.12%
93 hur 86 0.11%
94 några 85 0.11%
95 min 83 0.11%
96 vill 83 0.11%
97 herr 82 0.11%
98 aldrig 80 0.11%
99 par 80 0.11%
100 Malmsten 79 0.11%
101 voro 79 0.11%
102 dig 79 0.11%
103 satt 77 0.1%
104 säga 77 0.1%
105 andra 77 0.1%
106 76 0.1%
107 genom 75 0.1%
108 mycket 75 0.1%
109 hennes 74 0.1%
110 dag 74 0.1%
111 endast 73 0.1%
112 73 0.1%
113 åt 72 0.1%
114 fröken 72 0.1%
115 väl 71 0.09%
116 när 70 0.09%
117 ur 68 0.09%
118 fick 67 0.09%
119 kanske 66 0.09%
120 vet 65 0.09%
121 skall 65 0.09%
122 fram 64 0.09%
123 nog 64 0.09%
124 annat 63 0.08%
125 två 63 0.08%
126 ska 63 0.08%
127 någon 62 0.08%
128 tillbaka 61 0.08%
129 hos 61 0.08%
130 hela 61 0.08%
131 sista 60 0.08%
132 stora 58 0.08%
133 samma 58 0.08%
134 tog 57 0.08%
135 måste 57 0.08%
136 Griff 57 0.08%
137 er 57 0.08%
138 små 56 0.07%
139 sen 56 0.07%
140 ingen 55 0.07%
141 mellan 55 0.07%
142 hufvudet 54 0.07%
143 resten 53 0.07%
144 alltid 52 0.07%
145 lilla 52 0.07%
146 länge 52 0.07%
147 hvars 51 0.07%
148 ögonen 51 0.07%
149 Holm 49 0.07%
150 hvar 49 0.07%
151 kring 49 0.07%
152 redan 48 0.06%
153 liten 48 0.06%
154 stor 48 0.06%
155 sedan 47 0.06%
156 lif 47 0.06%
157 sina 47 0.06%
158 mitt 47 0.06%
159 hörde 46 0.06%
160 gjorde 45 0.06%
161 ögon 45 0.06%
162 går 45 0.06%
163 började 45 0.06%
164 nya 44 0.06%
165 liksom 44 0.06%
166 ser 44 0.06%
167 bort 44 0.06%
168 vidare 43 0.06%
169 fanns 43 0.06%
170 namn 43 0.06%
171 hvita 42 0.06%
172 ens 42 0.06%
173 ändå 42 0.06%
174 igen 42 0.06%
175 tror 42 0.06%
176 slog 41 0.05%
177 Ask 41 0.05%
178 annan 41 0.05%

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 Fata Morgana. En Stockholmsnovell by Henning Berger

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.