Ännu en million anekdoter by Carl-Henrik Rydberg : Difficulty Assessment for Swedish Learners

How difficult is Ännu en million anekdoter for Swedish learners? We have performed multiple tests on its full text (freely available here) of approximately 44,164, crunched all the numbers for you and present the results below.

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Difficulty Assessment Summary

We have estimated Ännu en million anekdoter to have a difficulty score of 67. Here're its scores:

Measure Score
easy difficult (1 - 100)
Overall Difficulty 67% 67
Vocabulary Difficulty 81% 81
Grammatical Difficulty 53% 53

Vocabulary Difficulty: Breakdown

81%

Vocabulary difficulty: 81%

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

Vocabulary difficulty breakdown for Ännu en million anekdoter: a test for Swedish top frequency vocabulary

We have also calculated the following approximate data on the vocabulary in Ännu en million anekdoter:

Measure Score
Measure Score
Number of words 44,164
Number of unique words 9,934
Number of recognized words for names/places/other entities 2,195
Number of very rare non-entity words 2,645
Number of sentences 7,028
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 9,735 words (where all the forms of the word are still counted as unique words) in Swedish to be able to read Ännu en million anekdoter without a dictionary and fully understand it.

Grammatical Difficulty: Breakdown

53%

Grammatical difficulty: 53%

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) 0.224934
Root type/Token Ratio (RTTR) 0.00000509316
Corrected type/Token Ratio (CTTR) 0.00000254658
MTLD Index 65
HDD Index 66
Yule's I Index 75
Lexical Diversity Index (MTLD + HD-D + Yule's I) 69

The type-token ratio (TTR) of Ännu en million anekdoter is 0.224934. 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 9,934, while the number of words is 44,164, so the TTR is 9,934 / 44,164 = 0.224934. 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, 9,934 / (44,164 * 44,164) = 0.00000509316), while in CTTR, it is divided by a square of the number of words, multiplied twice 9,934 / 2 * (44,164 * 44,164) = 0.00000254658). 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 69 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 53.

Other Information about Ännu en million anekdoter by Carl-Henrik Rydberg

We provide you a sample of the text below, however, the full text of the Ännu en million anekdoter is also available free of charge on our website.

Sample of text:

.. (nytt skratt) med de sjuka kreaturen. * Något för något. Händelsen föregår i Ryssland. En skomakare förärade en dag till czar Ivan Vasilievitsch en rofva af underbar storlek, såsom den vackraste present hvilken det stod i hans förmåga att gifva. Czaren mottog denna egendomliga gåfva, vedergällde skomakaren frikostigt, och befallde dessutom herrarne vid sitt hof att allesammans låta förfärdiga sina skodon hos honom och betala dem dubbelt mot det vanliga priset. En sniken hofman, — slägtet är icke sällsynt, — som såg på hvilket sätt czaren hade gengäldat en gåfva af så ringa värde, inbillade sig att genom att skänka czaren sin vackraste häst han också skulle få emottaga ...

Top most frequently used words in Ännu en million anekdoter by Carl-Henrik Rydberg*

Position Word Repetitions Part of all words
Position Word Repetitions Part of all words
1 en 1,127 2.55%
2 och 1,040 2.35%
3 att 1,008 2.28%
4 han 611 1.38%
5 567 1.28%
6 som 554 1.25%
7 det 535 1.21%
8 den 518 1.17%
9 af 511 1.16%
10 till 509 1.15%
11 jag 480 1.09%
12 för 455 1.03%
13 med 388 0.88%
14 sig 364 0.82%
15 är 353 0.8%
16 ett 309 0.7%
17 var 283 0.64%
18 sin 281 0.64%
19 icke 268 0.61%
20 265 0.6%
21 om 245 0.55%
22 hade 220 0.5%
23 har 215 0.49%
24 de 213 0.48%
25 man 211 0.48%
26 honom 206 0.47%
27 202 0.46%
28 men 178 0.4%
29 svarade 178 0.4%
30 skulle 168 0.38%
31 sade 164 0.37%
32 hans 162 0.37%
33 ni 157 0.36%
34 mig 156 0.35%
35 min 135 0.31%
36 hon 130 0.29%
37 du 129 0.29%
38 vid 119 0.27%
39 mycket 106 0.24%
40 henne 105 0.24%
41 frågade 104 0.24%
42 blef 101 0.23%
43 hvad 97 0.22%
44 sina 92 0.21%
45 från 91 0.21%
46 er 90 0.2%
47 inte 85 0.19%
48 gång 83 0.19%
49 under 81 0.18%
50 der 78 0.18%
51 skall 77 0.17%
52 efter 75 0.17%
53 öfver 72 0.16%
54 dag 72 0.16%
55 sitt 72 0.16%
56 kan 72 0.16%
57 kom 71 0.16%
58 följande 70 0.16%
59 ej 68 0.15%
60 dem 66 0.15%
61 vara 66 0.15%
62 detta 66 0.15%
63 än 65 0.15%
64 några 64 0.14%
65 ha 63 0.14%
66 upp 62 0.14%
67 eller 60 0.14%
68 år 59 0.13%
69 denna 59 0.13%
70 58 0.13%
71 åt 57 0.13%
72 någon 57 0.13%
73 hvilken 57 0.13%
74 sedan 56 0.13%
75 utan 56 0.13%
76 nu 55 0.12%
77 hos 54 0.12%
78 fick 54 0.12%
79 gick 54 0.12%
80 ut 53 0.12%
81 ville 52 0.12%
82 göra 52 0.12%
83 blifvit 51 0.12%
84 sjelf 51 0.12%
85 ty 50 0.11%
86 något 50 0.11%
87 alla 50 0.11%
88 här 50 0.11%
89 när 49 0.11%
90 vi 49 0.11%
91 hennes 49 0.11%
92 andra 49 0.11%
93 se 49 0.11%
94 herre 48 0.11%
95 hustru 48 0.11%
96 Ja 46 0.1%
97 mot 46 0.1%
98 väl 43 0.1%
99 ung 43 0.1%
100 Nej 42 0.1%
101 dig 42 0.1%
102 in 42 0.1%
103 kunde 41 0.09%
104 oss 41 0.09%
105 vill 41 0.09%
106 får 41 0.09%
107 varit 41 0.09%
108 Jo 40 0.09%
109 äro 39 0.09%
110 samma 39 0.09%
111 voro 38 0.09%
112 yttrade 38 0.09%
113 två 37 0.08%
114 helt 37 0.08%
115 hela 37 0.08%
116 bli 37 0.08%
117 gammal 37 0.08%
118 genom 37 0.08%
119 kommer 37 0.08%
120 går 36 0.08%
121 36 0.08%
122 fru 35 0.08%
123 taga 35 0.08%
124 tog 35 0.08%
125 ännu 35 0.08%
126 denne 35 0.08%
127 aldrig 34 0.08%
128 säga 34 0.08%
129 ord 33 0.07%
130 måste 33 0.07%
131 mina 33 0.07%
132 gaf 33 0.07%
133 mitt 33 0.07%
134 säger 32 0.07%
135 herr 31 0.07%
136 hvilka 31 0.07%
137 sätt 31 0.07%
138 annan 30 0.07%
139 såsom 30 0.07%
140 ju 30 0.07%
141 mer 30 0.07%
142 hr 29 0.07%
143 barn 29 0.07%
144 genast 29 0.07%
145 tidning 29 0.07%
146 gjorde 29 0.07%
147 annat 29 0.07%
148 första 29 0.07%
149 Gud 28 0.06%
150 andre 28 0.06%
151 ur 28 0.06%
152 hur 28 0.06%
153 många 28 0.06%
154 också 27 0.06%
155 liten 27 0.06%
156 kunna 27 0.06%
157 ser 27 0.06%
158 alldeles 27 0.06%
159 lät 26 0.06%
160 nog 26 0.06%
161 äfven 26 0.06%
162 gör 26 0.06%
163 far 26 0.06%
164 par 26 0.06%
165 tid 26 0.06%
166 ganska 26 0.06%
167 såg 26 0.06%
168 tillbaka 26 0.06%
169 Paris 25 0.06%
170 son 25 0.06%
171 utropade 25 0.06%
172 mannen 25 0.06%
173 allt 25 0.06%
174 fruntimmer 25 0.06%
175 litet 24 0.05%
176 god 24 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 Ännu en million anekdoter by Carl-Henrik Rydberg

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.