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Here are some examples of topics analysis using MeaningCloud API:
Extract all the possible topics of a text.
To show how to extract the topics we will use the following text as an example:
"Robert Downey Jr has topped Forbes magazine's annual list of the highest paid actors for the second year in a row. The 49-year-old star of the Iron Man and Avengers films made an estimated $75m over the past year, beating rivals Dwayne Johnson, Bradley Cooper, Chris Hemsworth and Leonardo DiCaprio."
Use the txt parameter to submit the text.
Choose with lang the language in which the text is going to be analyzed, in this case English, en.
Determine the language of the response body with ilang. This will be the language in which the response is returned, wether or not is the same of the analyzed text. In this case English, en.
Select a as the value for the tt parameter to extract all the possible topics.
Include your MeaningCloud license key as value for key parameter.
Choose an output format, for instance json as value for of.
Change the default value of the unknown words parameter, uw so the engine tries to find possible analysis when there are typos in the text.
Example using curl
curl -XPOST "https://api.meaningcloud.com/topics-2.0?key=<<YOUR OWN KEY>>&of=json&lang=en&ilang=en&txt=Robert%20Downey%20Jr%20has%20topped%20Forbes%20magazine%27s%20annual%20list%20of%20the%20highest%20paid%20actors%20for%20the%20second%20year%20in%20a%20row.%20The%2049-year-old%20star%20of%20the%20Iron%20Man%20and%20Avengers%20films%20made%20an%20estimated%20%2475m%20over%20the%20past%20year%2C%20beating%20rivals%20Dwayne%20Johnson%2C%20Bradley%20Cooper%2C%20Chris%20Hemsworth%20and%20Leonardo%20DiCaprio.&tt=a&uw=y"