but basically I will show you how and what I did in order to get where.
Arabic is a Semitic language. It has around 320 natives and about 60 million second-language speakers.
But there are estimates that say that Arabic is being spoken of about half a billion people worldwide.
It's an Afro-Asiatic language and one of the six official UN languages.
As Semitic languages, Arabic doesn't represent short vowels in normal script.
And words are derived using a root system.
That means that by changing vowels and adding pre or soft or circum fixes or infixes, we get different words.
This said, it has also a complex verbal morphology, like other Semitic languages as well.
Why should one learn media Arabic? In 2006 we find this quotation in a book, in a handbook of teaching Arabic.
When Arab newspapers and magazines are read, all kinds of information is found on the West.
To the contrary, when European newspapers and magazines are read, often only information on the Arab world gathered by people
who have not mastered the Arabic language is found.
Even the many views of Arabs on themselves found in Arabic newspapers and magazines are not reflected in the Western world.
Often only interpretations of the Arab world from a Western view are found.
So learning a language actually lets you gain a new world.
How to learn media Arabic?
The first Arabic magazine was founded in 1828.
And the first textbook from Western perspective was to follow in 1866, while the first word count followed in 1940.
Contemporary English materials for learning Arabic are HDN is media Arabic,
Jibali is media Arabic, a coursebook for reading Arabic news, and Lahlali is advanced media Arabic.
None of these publications enable you to learn media Arabic from a certain basis.
So they are written for specific institutions, by specific authors,
and it's hard if you, for example, learn Arabic at the University of Vienna, you don't have the same level
as if you'd have while studying Arabic with Professor Ashtyani.
So there are also smart learning materials, like from...
which unfortunately was based only on about 80,000 tokens, so the...
The sample is pretty small.
Candle's top thousand words are not the top thousand words of media Arabic, but the vocabulary for Ashtyani's publication.
And there is a Spanish textbook which is based on Brill's word count of 1940, so we should do something about that.
Pacwald and Parkinson were the first to publish an Arabic frequency dictionary by modern means,
like basing on a corpus of 30 million words, but it's for general Arabic based on prosaic Arabic.
So we start... I started collecting my corpus, which was a newspaper, a second one, and transcripts from Al Jazeera.
So I had about 23.5 million tokens.
I started extracting the plain text and put the text files together to normalize and edit the text,
and I started analyzing the text using Pacwald's Arabic morphologic analyzer, in short B-A-M-A.
Pacwald's output looks like this, so we have a token that was read in and all the possible solutions of lemmatizing it.
So, in fact, we have a word, and it can be read as Al-Kritar, or Al-Qattar, or Al-Qattar.
In media Arabic, context won't have herds or stone cutters or cutters, but will have mostly a Gaza Strip or the sector or section in terms of economics.
So, I first gathered all the possible lemmas per token in one line.
I calculated the line, or the lemmas at frequency.
This would be the token frequency count as a comparison, and we find several problems here.
For example, in the token list, we have male and female versions, like Al-Lati and Al-Ladi, both meaning this in English.
So, we have the female and the male form of this in Arabic.
In the lemmas at frequencies, we have the problem that both these, nice example, are in separate lines.
In separate lines, it's okay, and we have to merge these.
So, we also have sub lemmas like man one and man two, man one being who, and man two being who as a relative pronoun, for example, the man who did something and who did something.
So, we have to remove sub lemmas first because we'll analyze them in the end for the dictionary.
We remove duplicates in one line, and we merge the lemmas at frequencies.
So, we merge the frequency of Al-Ladi, the male version and the female version, to get the frequency of this in English, as in English translation.
So, we break up the lemmas at, and then we estimate for each lemma the frequency in Google News as a primary key to work with.
Then, we analyze each lemma fully using Buck-Walter's Morphologic Analyzer again, so that we get to analyze the material at the end manually in a top-down manner.
The morphological ambiguity rate being three, that means we have mostly three possibilities of analyzing a word.
But, in the dictionary form, in the semantical part, we have to think, like, what would this word mean, or why would one as what?
In what meaning, one would use that word in a media context, like retin, the example I gave.
We should only put sector and strip, and not cutter or herds in our context.
I had to estimate the vocabulary items needed for the level B2 of European language learners, and I estimated that I'm using some estimations for Greek and Korean, Japanese and Chinese, and found that it should be around three and a half thousand lemmata.
So, I extracted these three and a half thousand lemmas, including proper names and verbal nouns, including proper names because everything that a student can recognize in the text is good for him.
So, why bother about looking for raza in an Arabic dictionary if you learn that raza denotes Gaza in Palestine?
And then I had to sort the lemmas by roots manually. So, actually, the material in an Excel sheet looked like this.
So, I have a word, the corpus where it came from, the lemma form, part of speech tagging, and the English meaning, and pre-layetting it for latex.
The result was that I got the top three and a half thousand lemmas of written and oral media Arabic, that I could extract neologisms by word length and word patterns as well from my corpus.
I could extract multi-word items by angram analyzes, and I could find collocations. Collocation is something like the UN.
The anti-Nazi union in German is a collocation in Arabic. It would be alumma almutahida, so you have that form, which you don't find normally in a dictionary.
There are more complicated forms, but just as a matter to explain it.
And I could extract a discursive glossary, since I used oral text as well, including dialectal variants.
For example, this would be sahula. It's true and it's not.
Or, muxahede maudorana, depends on the speaker. That's not our topic.
That is not our topic, but that's not our topic. It's dialectal.
Or some new words like antiviral, modalil virus. You won't find that in an Arabic dictionary.
Then I had to calculate the text coverage.
And I used 10 texts of Lahlali's Advanced Media Arabic.
And what I basically found was that my dictionary covers about 95% of non-trivial recent media texts.
And it reduces the number of lookups in dictionaries for a student to 24 plus minus 10 times, for texts of an average length of 550 words.
And the Lahlali's can be used as a handout for students to level their differences in vocabulary.
And the corpus material can be used for basic searches.
But it's not only a search process, but it can also be seen as a learning process.
Because students can learn vocabulary and collocations in an explorative manner by searching for them and seeing how they are used in context.
And in writing assignments, for example, the material can be used to make idiomatic corrections in writing assignments.
For example, by means of violence, which verb takes which proposition, in what meaning.
And essentially it makes Arabic learnable.
And hopefully this quotation may change as soon as possible to something else.
Thank you.