Film by Hjalmar Bergman : Difficulty Assessment for Swedish Learners

How difficult is Film for Swedish learners? We have performed multiple tests on its full text (freely available here) of approximately 121,290, crunched all the numbers for you and present the results below.

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Difficulty Assessment Summary

We have estimated Film to have a difficulty score of 52. Here're its scores:

Measure Score
easy difficult (1 - 100)
Overall Difficulty 52% 52
Vocabulary Difficulty 54% 54
Grammatical Difficulty 51% 51

Vocabulary Difficulty: Breakdown

54%

Vocabulary difficulty: 54%

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

Vocabulary difficulty breakdown for Film: a test for Swedish top frequency vocabulary

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

Measure Score
Measure Score
Number of words 121,290
Number of unique words 15,630
Number of recognized words for names/places/other entities 4,929
Number of very rare non-entity words 2,145
Number of sentences 19,744
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 15,317 words (where all the forms of the word are still counted as unique words) in Swedish to be able to read Film without a dictionary and fully understand it.

Grammatical Difficulty: Breakdown

51%

Grammatical difficulty: 51%

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) 0.128865
Root type/Token Ratio (RTTR) 0.00000106245
Corrected type/Token Ratio (CTTR) 0.000000531226
MTLD Index 62
HDD Index 65
Yule's I Index 70
Lexical Diversity Index (MTLD + HD-D + Yule's I) 66

The type-token ratio (TTR) of Film is 0.128865. 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 15,630, while the number of words is 121,290, so the TTR is 15,630 / 121,290 = 0.128865. 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, 15,630 / (121,290 * 121,290) = 0.00000106245), while in CTTR, it is divided by a square of the number of words, multiplied twice 15,630 / 2 * (121,290 * 121,290) = 0.000000531226). 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 66 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 51.

Other Information about Film by Hjalmar Bergman

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

Sample of text:

Och han rullar åter mot väggen med täcket upp över öronen. Det kan behövas - men hjälper inte. Gumman är besluten att väcka honom till sina plikter och sina synders besinnelse. Så tar hon då ett jakthorn från väggen och med kinderna uppblåsta som domedagens änglar stöter hon i basun. - Åhå ja ja, suckar löjtnanten. Friden är slut Han sätter sig upp och gnuggar ögonen. Domedagsängeln åter tar efter basunen till med predikan. Tänk vad han var rar förr i tiden! Och hur har inte de usla kvinnfolken skämt bort honom! Då sätter sig herr löjtnanten indignerad upp och slänger käft med gumman, yttrande: - Hon har ingenting att säga, Olsson! Hon var en av de första kvinnorna i mitt liv och hon bar mig på sina händer, gamla kelegris! ...

Top most frequently used words in Film by Hjalmar Bergman*

Position Word Repetitions Part of all words
Position Word Repetitions Part of all words
1 och 4,737 3.91%
2 en 2,196 1.81%
3 han 2,081 1.72%
4 att 1,808 1.49%
5 1,583 1.31%
6 den 1,565 1.29%
7 som 1,545 1.27%
8 sig 1,500 1.24%
9 med 1,426 1.18%
10 är 1,239 1.02%
11 till 1,225 1.01%
12 det 1,165 0.96%
13 hon 1,140 0.94%
14 av 1,084 0.89%
15 ett 884 0.73%
16 honom 880 0.73%
17 för 880 0.73%
18 sin 785 0.65%
19 de 701 0.58%
20 men 685 0.56%
21 har 675 0.56%
22 henne 636 0.52%
23 inte 605 0.5%
24 581 0.48%
25 hans 529 0.44%
26 om 505 0.42%
27 mot 476 0.39%
28 fram 468 0.39%
29 upp 457 0.38%
30 står 409 0.34%
31 hennes 398 0.33%
32 nu 391 0.32%
33 kommer 387 0.32%
34 över 387 0.32%
35 386 0.32%
36 säger 378 0.31%
37 tar 375 0.31%
38 in 367 0.3%
39 vid 356 0.29%
40 går 342 0.28%
41 ut 330 0.27%
42 jag 328 0.27%
43 där 311 0.26%
44 från 306 0.25%
45 ser 298 0.25%
46 sitt 285 0.23%
47 dem 284 0.23%
48 sina 264 0.22%
49 var 249 0.21%
50 du 249 0.21%
51 åt 229 0.19%
52 icke 224 0.18%
53 än 223 0.18%
54 blir 222 0.18%
55 gör 216 0.18%
56 man 212 0.17%
57 kan 210 0.17%
58 Elsa 203 0.17%
59 ur 203 0.17%
60 efter 202 0.17%
61 hand 195 0.16%
62 min 194 0.16%
63 herr 194 0.16%
64 Marten 191 0.16%
65 vill 189 0.16%
66 ej 184 0.15%
67 själv 182 0.15%
68 dörren 181 0.15%
69 båda 174 0.14%
70 får 172 0.14%
71 Felix 171 0.14%
72 andra 169 0.14%
73 något 169 0.14%
74 handen 168 0.14%
75 mig 168 0.14%
76 fru 168 0.14%
77 Merethe 164 0.14%
78 några 164 0.14%
79 eller 163 0.13%
80 under 159 0.13%
81 ha 159 0.13%
82 vänder 157 0.13%
83 åter 157 0.13%
84 bort 156 0.13%
85 Sven 154 0.13%
86 väl 144 0.12%
87 vad 143 0.12%
88 skall 141 0.12%
89 sitter 141 0.12%
90 se 137 0.11%
91 genom 135 0.11%
92 huvudet 132 0.11%
93 hade 132 0.11%
94 Gycklaren 132 0.11%
95 måste 132 0.11%
96 utan 131 0.11%
97 skulle 129 0.11%
98 Ruggiero 129 0.11%
99 128 0.11%
100 kring 127 0.1%
101 komma 126 0.1%
102 framför 126 0.1%
103 ansikte 124 0.1%
104 vara 124 0.1%
105 när 121 0.1%
106 lilla 119 0.1%
107 ned 118 0.1%
108 alla 116 0.1%
109 ger 116 0.1%
110 liten 114 0.09%
111 allt 114 0.09%
112 mycket 111 0.09%
113 leende 111 0.09%
114 tillbaka 111 0.09%
115 blick 109 0.09%
116 smula 108 0.09%
117 händer 107 0.09%
118 ska 106 0.09%
119 ju 105 0.09%
120 steg 104 0.09%
121 dig 104 0.09%
122 drar 103 0.08%
123 dock 101 0.08%
124 lägger 101 0.08%
125 börjar 100 0.08%
126 mellan 99 0.08%
127 flickan 97 0.08%
128 slår 97 0.08%
129 ni 96 0.08%
130 helt 96 0.08%
131 ögonen 96 0.08%
132 någon 95 0.08%
133 stor 94 0.08%
134 betraktar 94 0.08%
135 fönstret 94 0.08%
136 hur 93 0.08%
137 långsamt 93 0.08%
138 håller 92 0.08%
139 ner 92 0.08%
140 stiger 92 0.08%
141 91 0.08%
142 ännu 91 0.08%
143 Wunderlich 91 0.08%
144 rummet 89 0.07%
145 hela 89 0.07%
146 hastigt 88 0.07%
147 Eneman 88 0.07%
148 Inez 87 0.07%
149 Blinde 86 0.07%
150 ögonblick 86 0.07%
151 gång 86 0.07%
152 detta 85 0.07%
153 huvud 85 0.07%
154 sätter 84 0.07%
155 sidan 84 0.07%
156 göra 84 0.07%
157 annat 83 0.07%
158 Ursula 81 0.07%
159 stannar 80 0.07%
160 äro 80 0.07%
161 just 80 0.07%
162 ta 80 0.07%
163 samma 80 0.07%
164 denna 80 0.07%
165 emot 80 0.07%
166 mer 80 0.07%
167 omkring 79 0.07%
168 faller 79 0.07%
169 vet 78 0.06%
170 svarar 77 0.06%
171 kastar 77 0.06%
172 bakom 77 0.06%
173 också 76 0.06%
174 lyfter 75 0.06%
175 Tora 75 0.06%
176 stirrar 75 0.06%
177 er 75 0.06%
178 även 75 0.06%
179 ty 73 0.06%
180 här 72 0.06%
181 Hortense 72 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 Film by Hjalmar Bergman

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.