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Request

Endpoint:

POST
https://api.meaningcloud.com/reputation-1.0


If you are working with an on-premises installation, you will need to substitute api.meaningcloud.com by your own server address.

Content-Type:

multipart/form-data

Parameters:

NameDescriptionValuesNotes
keyAuthorization key for using MeaningCloud services. Create an account for free to create your key.Required
ofOutput format.json xmlOptional. Default:json
txtThe text format parameter specifies if the text included in the txt parameter uses markup language that needs to be interpreted (known HTML tags and HTML code will be interpreted, and unknown tags will be ignored).plain / markupOptional. Default: txtf=plain
txtfThe text format parameter specifies if the text included in the txt parameter uses markup language that needs to be interpreted (known HTML tags and HTML code will be interpreted, and unknown tags will be ignored).UTF-8 encoded text (plain text, HTML or XML).Required
modelClassification model to use. It will define into which categories the text may be classified.BusinessRep_es: model for business reputation in Spanish. There's more information on its categories in this section.Required.
udThe user dictionary allows to include user-defined entities and concepts in the sentiment analysis. It provides a mechanism to adapt the process to focus on specific domains or on terms relevant to a user's interests, either to increase the precision in any of the domains already taken into account in our ontology to include a new one, or just to add a new semantic meaning to known terms.Name of your user dictionaries.Optional. Default: ud=""
rtThis parameter indicates how reliable the text to analyze is (as far as spelling, typography, etc. are concerned), and influences how strict the engine will be when it comes to take these factors into account in the analysis.y: enabled for all resources
u: enabled just for user dictionary
n: disabled
Optional. Default: rt=n
inferDeal with inferences. This feature adds a stage to the entities extractions in which the engine tries to infere knowledge: on the one hand, it tries to resolve correferences and on the other hand, it tries to establish a relationship between companies and products in order to improve categorization.y: enabled
n: disabled
Optional. Default: infer=n