Genom norra Amerikas förenta stater by P. P. Waldenström : Difficulty Assessment for Swedish Learners

How difficult is Genom norra Amerikas förenta stater for Swedish learners? We have performed multiple tests on its full text (freely available here) of approximately 133,371, crunched all the numbers for you and present the results below.

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Difficulty Assessment Summary

We have estimated Genom norra Amerikas förenta stater to have a difficulty score of 64. Here're its scores:

Measure Score
easy difficult (1 - 100)
Overall Difficulty 64% 64
Vocabulary Difficulty 72% 72
Grammatical Difficulty 56% 56

Vocabulary Difficulty: Breakdown

72%

Vocabulary difficulty: 72%

This score has been calculated based on frequency vocabulary (the top most frequently used words in Swedish). It combines various measures of Genom norra Amerikas förenta stater'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 Genom norra Amerikas förenta stater:

Vocabulary difficulty breakdown for Genom norra Amerikas förenta stater: a test for Swedish top frequency vocabulary

We have also calculated the following approximate data on the vocabulary in Genom norra Amerikas förenta stater:

Measure Score
Measure Score
Number of words 133,371
Number of unique words 16,895
Number of recognized words for names/places/other entities 6,226
Number of very rare non-entity words 9,074
Number of sentences 20,080
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 16,557 words (where all the forms of the word are still counted as unique words) in Swedish to be able to read Genom norra Amerikas förenta stater without a dictionary and fully understand it.

Grammatical Difficulty: Breakdown

56%

Grammatical difficulty: 56%

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 8
Type/Token Ratio (TTR) 0.126677
Root type/Token Ratio (RTTR) 0.000000949807
Corrected type/Token Ratio (CTTR) 0.000000474904
MTLD Index 66
HDD Index 68
Yule's I Index 80
Lexical Diversity Index (MTLD + HD-D + Yule's I) 71

The type-token ratio (TTR) of Genom norra Amerikas förenta stater is 0.126677. 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 16,895, while the number of words is 133,371, so the TTR is 16,895 / 133,371 = 0.126677. 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, 16,895 / (133,371 * 133,371) = 0.000000949807), while in CTTR, it is divided by a square of the number of words, multiplied twice 16,895 / 2 * (133,371 * 133,371) = 0.000000474904). 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 56.

Other Information about Genom norra Amerikas förenta stater by P. P. Waldenström

We provide you a sample of the text below, however, the full text of the Genom norra Amerikas förenta stater is also available free of charge on our website.

Sample of text:

Tabernaklet ser ut såsom ett på längden ituskuret äggskal, hvilande på pelare, mellan hvilka stora portar äro insatta. Det är utan tvifvel den största gudstjenstlokal, som finnes på jorden. Läktaren, som går längs efter bägge långsidorna och ena kortsidan af huset, är nära 500 fot lång och har 9 bänkrader. Tabernaklet i sin helhet har sittplatser för tio tusen menniskor. Salen är ett riktigt haf. Några prydnader förekomma icke i den samma. Allting är mycket enkelt och stillöst. I ena änden är på väggen målad en stor bikupa, hvilket lär vara territoriet Utahs vapen. Och sant är, att ...

Top most frequently used words in Genom norra Amerikas förenta stater by P. P. Waldenström*

Position Word Repetitions Part of all words
Position Word Repetitions Part of all words
1 och 3,183 2.39%
2 att 2,835 2.13%
3 en 2,534 1.9%
4 som 1,962 1.47%
5 1,777 1.33%
6 det 1,757 1.32%
7 af 1,725 1.29%
8 jag 1,578 1.18%
9 för 1,491 1.12%
10 de 1,479 1.11%
11 till 1,456 1.09%
12 den 1,437 1.08%
13 är 1,185 0.89%
14 var 1,132 0.85%
15 icke 1,061 0.8%
16 med 1,006 0.75%
17 ett 905 0.68%
18 hade 828 0.62%
19 795 0.6%
20 man 732 0.55%
21 om 725 0.54%
22 han 711 0.53%
23 sig 683 0.51%
24 der 651 0.49%
25 vi 623 0.47%
26 har 615 0.46%
27 mig 599 0.45%
28 mycket 565 0.42%
29 skulle 496 0.37%
30 från 430 0.32%
31 dem 418 0.31%
32 äro 395 0.3%
33 hafva 393 0.29%
34 än 380 0.28%
35 men 375 0.28%
36 vid 362 0.27%
37 kan 355 0.27%
38 öfver 349 0.26%
39 vara 342 0.26%
40 Amerika 334 0.25%
41 äfven 302 0.23%
42 nu 302 0.23%
43 eller 301 0.23%
44 voro 287 0.22%
45 andra 286 0.21%
46 detta 278 0.21%
47 utan 277 0.21%
48 ut 268 0.2%
49 264 0.2%
50 stor 259 0.19%
51 denna 259 0.19%
52 alla 257 0.19%
53 sin 252 0.19%
54 samma 248 0.19%
55 när 248 0.19%
56 såsom 232 0.17%
57 svenska 229 0.17%
58 229 0.17%
59 många 226 0.17%
60 oss 223 0.17%
61 stora 220 0.16%
62 måste 216 0.16%
63 kunde 215 0.16%
64 min 215 0.16%
65 år 212 0.16%
66 samt 212 0.16%
67 genom 212 0.16%
68 under 206 0.15%
69 mer 201 0.15%
70 någon 201 0.15%
71 hvad 201 0.15%
72 dessa 199 0.15%
73 se 196 0.15%
74 Sverige 195 0.15%
75 honom 195 0.15%
76 sina 191 0.14%
77 tusen 190 0.14%
78 omkring 189 0.14%
79 några 189 0.14%
80 upp 189 0.14%
81 Chicago 187 0.14%
82 efter 184 0.14%
83 göra 183 0.14%
84 något 179 0.13%
85 sade 177 0.13%
86 här 176 0.13%
87 kunna 175 0.13%
88 hans 174 0.13%
89 också 170 0.13%
90 ock 170 0.13%
91 varit 167 0.13%
92 hon 167 0.13%
93 svensk 166 0.12%
94 staden 166 0.12%
95 skall 165 0.12%
96 hela 158 0.12%
97 sedan 157 0.12%
98 dock 154 0.12%
99 hvilka 151 0.11%
100 väl 143 0.11%
101 sitt 142 0.11%
102 alldeles 142 0.11%
103 ganska 142 0.11%
104 ej 141 0.11%
105 blef 141 0.11%
106 allt 140 0.1%
107 amerikanska 140 0.1%
108 ord 138 0.1%
109 deras 135 0.1%
110 bland 135 0.1%
111 New 135 0.1%
112 gång 134 0.1%
113 130 0.1%
114 dess 130 0.1%
115 annat 130 0.1%
116 in 130 0.1%
117 huru 129 0.1%
118 kom 128 0.1%
119 Gud 127 0.1%
120 komma 124 0.09%
121 dollars 123 0.09%
122 två 123 0.09%
123 första 122 0.09%
124 sid 119 0.09%
125 hvilken 119 0.09%
126 flere 116 0.09%
127 åt 116 0.09%
128 svenskar 116 0.09%
129 personer 115 0.09%
130 säga 115 0.09%
131 fram 114 0.09%
132 mil 113 0.08%
133 hos 111 0.08%
134 gick 109 0.08%
135 York 108 0.08%
136 gjorde 107 0.08%
137 ned 106 0.08%
138 sätt 105 0.08%
139 land 105 0.08%
140 mellan 105 0.08%
141 hus 104 0.08%
142 ville 101 0.08%
143 sådan 101 0.08%
144 resa 101 0.08%
145 nämligen 99 0.07%
146 dag 99 0.07%
147 ju 99 0.07%
148 mina 99 0.07%
149 ligger 99 0.07%
150 fot 98 0.07%
151 sådana 97 0.07%
152 endast 96 0.07%
153 kommo 95 0.07%
154 stort 94 0.07%
155 våra 93 0.07%
156 blifva 93 0.07%
157 hvilket 93 0.07%
158 derför 92 0.07%
159 hem 92 0.07%
160 tid 92 0.07%
161 aldrig 91 0.07%
162 ur 91 0.07%
163 dit 90 0.07%
164 mot 90 0.07%
165 fick 90 0.07%
166 mindre 89 0.07%
167 finnes 89 0.07%
168 nog 89 0.07%
169 svarade 86 0.06%
170 såg 85 0.06%
171 blifvit 85 0.06%
172 kommer 85 0.06%
173 godt 84 0.06%
174 vill 83 0.06%
175 Guds 83 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 Genom norra Amerikas förenta stater by P. P. Waldenström

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.