Vett och ovett by Alfred Hedenstierna : Difficulty Assessment for Swedish Learners

How difficult is Vett och ovett for Swedish learners? We have performed multiple tests on its full text (freely available here) of approximately 65,593, crunched all the numbers for you and present the results below.

Read the Full Text Now for Free!

Difficulty Assessment Summary

We have estimated Vett och ovett to have a difficulty score of 75. Here're its scores:

Measure Score
easy difficult (1 - 100)
Overall Difficulty 75% 75
Vocabulary Difficulty 94% 94
Grammatical Difficulty 57% 57

Vocabulary Difficulty: Breakdown

94%

Vocabulary difficulty: 94%

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

Vocabulary difficulty breakdown for Vett och ovett: a test for Swedish top frequency vocabulary

We have also calculated the following approximate data on the vocabulary in Vett och ovett:

Measure Score
Measure Score
Number of words 65,593
Number of unique words 14,444
Number of recognized words for names/places/other entities 2,721
Number of very rare non-entity words 5,115
Number of sentences 8,670
Average number of words/sentence 8

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 14,155 words (where all the forms of the word are still counted as unique words) in Swedish to be able to read Vett och ovett 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 5
Coleman-Liau Index 9
Type/Token Ratio (TTR) 0.220206
Root type/Token Ratio (RTTR) 0.00000335716
Corrected type/Token Ratio (CTTR) 0.00000167858
MTLD Index 71
HDD Index 67
Yule's I Index 75
Lexical Diversity Index (MTLD + HD-D + Yule's I) 71

The type-token ratio (TTR) of Vett och ovett is 0.220206. 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 14,444, while the number of words is 65,593, so the TTR is 14,444 / 65,593 = 0.220206. 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, 14,444 / (65,593 * 65,593) = 0.00000335716), while in CTTR, it is divided by a square of the number of words, multiplied twice 14,444 / 2 * (65,593 * 65,593) = 0.00000167858). 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 5, making it understandable for 5-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 71 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 Vett och ovett by Alfred Hedenstierna

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

Sample of text:

Fönsterlufternas värde i sanitärt hänseende är obestäm dt och mycket varierande. En af mina vänner, hvilken jag i och för utarbetandet af denna vetenskapliga afhandling frågat om saken, svarade: »Vid Kungsgatan i Wexiö finnes ett par fönsterlufter, hvilka, när jag går förbi dem, på mig utöfva en högst obehaglig inverkan. Jag fryser och svettas, ångrar bitterligen alla punschhalfvor jag förtärt och alla glada aftnar jag tillbragt med nöjets prestinnor, blir ledsen vidlifvet och önskar ändå så innerligt, att tiden ville stå stilla i sin flygt. Innanför de fönsterlufterna bor Skånes enskilda banks afdelningskontor, och jag har många aflånga papper der. Vid Storgatan finnes åter en fönsterluft, som kommer mitt sinne att skälfva af bäfvande fröjd, hvar gång jag passerar den. Mina steg bli spänstigare, hjertat arbetar raskare, pulsarne glöda, och jag skulle, för att i en ...

Top most frequently used words in Vett och ovett by Alfred Hedenstierna*

Position Word Repetitions Part of all words
Position Word Repetitions Part of all words
1 och 2,590 3.95%
2 att 1,298 1.98%
3 en 1,125 1.72%
4 949 1.45%
5 det 895 1.36%
6 som 853 1.3%
7 för 775 1.18%
8 af 704 1.07%
9 han 682 1.04%
10 med 645 0.98%
11 632 0.96%
12 den 626 0.95%
13 till 568 0.87%
14 jag 564 0.86%
15 de 518 0.79%
16 är 508 0.77%
17 om 459 0.7%
18 inte 440 0.67%
19 ett 426 0.65%
20 sig 396 0.6%
21 men 368 0.56%
22 var 365 0.56%
23 hon 308 0.47%
24 hade 291 0.44%
25 har 278 0.42%
26 man 267 0.41%
27 skulle 256 0.39%
28 254 0.39%
29 sin 241 0.37%
30 vid 236 0.36%
31 eller 207 0.32%
32 när 200 0.3%
33 mig 191 0.29%
34 der 174 0.27%
35 min 159 0.24%
36 från 155 0.24%
37 vi 154 0.23%
38 än 154 0.23%
39 honom 154 0.23%
40 ha 153 0.23%
41 nu 153 0.23%
42 hans 151 0.23%
43 kan 145 0.22%
44 du 141 0.21%
45 icke 141 0.21%
46 alla 136 0.21%
47 aldrig 136 0.21%
48 öfver 128 0.2%
49 år 127 0.19%
50 ty 123 0.19%
51 bara 122 0.19%
52 sina 121 0.18%
53 någon 118 0.18%
54 utan 114 0.17%
55 efter 112 0.17%
56 vara 112 0.17%
57 sitt 109 0.17%
58 dem 107 0.16%
59 106 0.16%
60 mycket 103 0.16%
61 under 103 0.16%
62 något 102 0.16%
63 in 99 0.15%
64 kunde 98 0.15%
65 ut 95 0.14%
66 skall 95 0.14%
67 allt 92 0.14%
68 henne 92 0.14%
69 också 92 0.14%
70 såsom 91 0.14%
71 hvad 89 0.14%
72 bli 89 0.14%
73 sjelf 85 0.13%
74 kom 85 0.13%
75 gång 84 0.13%
76 fick 83 0.13%
77 upp 83 0.13%
78 åt 82 0.13%
79 hennes 80 0.12%
80 väl 80 0.12%
81 lilla 79 0.12%
82 varit 78 0.12%
83 andra 77 0.12%
84 alldeles 74 0.11%
85 se 74 0.11%
86 sa 73 0.11%
87 ännu 73 0.11%
88 hvilken 71 0.11%
89 oss 70 0.11%
90 äro 70 0.11%
91 kunna 70 0.11%
92 här 69 0.11%
93 två 68 0.1%
94 stora 68 0.1%
95 får 68 0.1%
96 alltid 67 0.1%
97 några 66 0.1%
98 gick 66 0.1%
99 vill 65 0.1%
100 sedan 65 0.1%
101 samt 64 0.1%
102 blef 64 0.1%
103 ni 63 0.1%
104 många 63 0.1%
105 62 0.09%
106 hela 62 0.09%
107 genom 58 0.09%
108 herr 57 0.09%
109 vår 57 0.09%
110 små 57 0.09%
111 våra 57 0.09%
112 göra 56 0.09%
113 fått 56 0.09%
114 barn 55 0.08%
115 ingen 55 0.08%
116 par 54 0.08%
117 mera 54 0.08%
118 första 53 0.08%
119 mot 52 0.08%
120 ur 51 0.08%
121 detta 51 0.08%
122 säga 50 0.08%
123 blir 50 0.08%
124 äfven 50 0.08%
125 bra 50 0.08%
126 gamla 49 0.07%
127 godt 49 0.07%
128 mitt 48 0.07%
129 ju 48 0.07%
130 vet 48 0.07%
131 verlden 47 0.07%
132 lika 47 0.07%
133 denna 47 0.07%
134 dig 47 0.07%
135 länge 46 0.07%
136 Ja 46 0.07%
137 ej 46 0.07%
138 dessa 45 0.07%
139 ville 45 0.07%
140 liten 45 0.07%
141 voro 45 0.07%
142 ändå 44 0.07%
143 Malena 44 0.07%
144 tid 44 0.07%
145 hvilka 44 0.07%
146 nog 43 0.07%
147 mer 43 0.07%
148 huru 43 0.07%
149 bättre 42 0.06%
150 hos 42 0.06%
151 lif 41 0.06%
152 Karl 41 0.06%
153 hvar 41 0.06%
154 gjort 41 0.06%
155 samma 41 0.06%
156 gjorde 41 0.06%
157 komma 40 0.06%
158 hem 40 0.06%
159 dag 40 0.06%
160 dock 40 0.06%
161 stor 39 0.06%
162 såg 39 0.06%
163 låta 39 0.06%
164 annat 39 0.06%
165 hjerta 39 0.06%
166 pappa 39 0.06%
167 litet 39 0.06%
168 annan 38 0.06%
169 gammal 38 0.06%
170 din 38 0.06%
171 mina 38 0.06%
172 tre 37 0.06%
173 lille 37 0.06%
174 både 37 0.06%
175 just 37 0.06%
176 sade 37 0.06%
177 rigtigt 37 0.06%
178 hvarje 36 0.05%
179 lite 36 0.05%
180 folk 36 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 Vett och ovett by Alfred Hedenstierna

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.