Classify articles by audience age group

Hi all

Thanks for reading my project.

We can generally say articles in magazines and newspapers can be classified by age range.

For example:

- the articles in "Cosmopolitan" magazine are aimed at 18 - 35 year olds.

- the articles in the "Financial Times" are aimed at 36 - 50, or 50+.

- the articles in "Readers Digest" are aimed at 50+.

- the articles in the "New York Times" are aimed at 18 - 35, 36 - 50, and 50+.

- the articles in "Vice" are aimed at 18 - 35.

So, sometimes there is an obvious target age, and other times it is more general.

Typically a certain type of language is used for each age group. For example, we could have three articles about healthy eating. But each one could be targeted at a different age group. Or could be targeted at all age groups. Therefore I do not want to classify the articles according to topic, but rather by the type of language used.

I need you to create a script/model which can detect the target age group for articles. We would input an article, and you would output the age range(s).

We need 60% - 80% accuracy.

We want to use these age ranges:

18 - 35

36 - 50


Please bid stating what you need from me to get started. I will ignore automated bids.

You must use Python 3.x.


Compétences : Apprentissage Automatique, Python

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Concernant l'employeur :
( 8 commentaires ) Hong Kong, Hong Kong

Nº du projet : #17109134

32 freelance font une offre moyenne de $443 pour ce travail


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Hi. What will be the format of the article? Is it a text file or a web page. Sending some samples will be a good idea. I will scrape some pages from the above data sources Cosmopolitan, FT, NYT etc.. and build the m Plus

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