Corporate Reputation Response

Response

The output contains information about the status of the request. Ultimately, it summarizes the reputational analysis of the text across three distinct axes. In the first instance, the entities (i.e., companies) detected in the text are obtained. Second, the reputational dimensions (categories) affecting each of the entities are output, each with an associated polarity. Finally, the global polarity for each entity is included, which in turn can be used as an indication as to whether the given text will likely have a positive, negative, neutral or no effect on the reputation of each of the entities detected in the text. Any phrases that have been relevant in the decision-making process are also output.

The information provided is the same for the different output formats and the naming convention used for all fields is lowercase_separated_by_underscore.

Response output

These are the fields included in the response document.

Name Description

Name	Description
`status`	Contains information about the extraction process and whether it has finished successfully. It is formed by a status code (`code`), a natural number that identifies the result, and a message (`msg`), a string describing the result. In addition, the field (`credits`) contains a natural number that indicates the credits consumed in the request and (`remaining_credits`) shows the number of credits left to the user to get to the credit limit. You can find all the possible status codes returned by the API with an explanation and tips on how to manage them in our error codes catalog. Did you know...? Only the successful requests to the API will consume credits. In other words, the `credits` specified in the answer will only count as credits consumed when `code=0`.
`entity_list`	List of the entities identified in the text. In the case that no entity is detected in the text and if no input focus has been specified, a special entity _DEFAULT_ will be obtained in order to obtain general information from the whole text. Each one will be represented by an element `entity`, which will contain the following fields: `id`: ID of the entity. This ID will correspond to its senseID in the resources. If the entity has been detected in the analysis, the ID will be specifically created for that analysis and will begin by two underscores. `form`: main form of the entity. `type`: Ontology type of the entity. Refer to Organizations according to MeaningCloud's ontology. By default: Media Companies, Government Organizations, Institutes, Military Organizations and Stock Markets are not considered to avoid excessive noise). If required, they can be included using the filter input param. `polarity`: global polarity of the entity. Possible values: P+: strong positive P: positive NEU: neutral N: negative N+: strong negative NONE: without polarity `category_list`: list of reputational categories in which the entity is classified. Each category is represented by a category object.

status

Contains information about the extraction process and whether it has finished successfully. It is formed by a status code (code), a natural number that identifies the result, and a message (msg), a string describing the result. In addition, the field (credits) contains a natural number that indicates the credits consumed in the request and (remaining_credits) shows the number of credits left to the user to get to the credit limit.

You can find all the possible status codes returned by the API with an explanation and tips on how to manage them in our error codes catalog.

Did you know...?

Only the successful requests to the API will consume credits. In other words, the credits specified in the answer will only count as credits consumed when code=0.

entity_list

List of the entities identified in the text. In the case that no entity is detected in the text and if no input focus has been specified, a special entity _DEFAULT_ will be obtained in order to obtain general information from the whole text. Each one will be represented by an element entity, which will contain the following fields:

id: ID of the entity. This ID will correspond to its senseID in the resources. If the entity has been detected in the analysis, the ID will be specifically created for that analysis and will begin by two underscores.
form: main form of the entity.
type: Ontology type of the entity. Refer to Organizations according to MeaningCloud's ontology. By default: Media Companies, Government Organizations, Institutes, Military Organizations and Stock Markets are not considered to avoid excessive noise). If required, they can be included using the filter input param.
polarity: global polarity of the entity. Possible values:
- P+: strong positive
- P: positive
- NEU: neutral
- N: negative
- N+: strong negative
- NONE: without polarity
category_list: list of reputational categories in which the entity is classified. Each category is represented by a category object.

Category element

These are the fields included in each category element.

Name	Description
`code`	category code
`label`	category description
`polarity`	polarity associated to the category
`abs_relevance`	absolute relevance value of the category
`relat_relevance`	relative relevance value of the category, a number in the 0-100% range, and computed with respect to the top ranked result
`sentence_list`	list of sentences in which the text is divided. Each sentence is represented by a sentence object. `text`: sentence text `inip`: position of the first character of the sentence (zero indexed). `endp`: positions of the last character of the sentence (zero indexed).

Response example

Endesa is building the largest photovoltaic project for self-consumption in the Balearic Islands

{
    "status": {
        "code": 0,
        "msg": "OK",
	"credits": 1
    },
    "entity_list": [
        {
            "id": "60f9a019a5",
            "form": "Endesa",
            "type": "Top>Organization>Company>UtilitiesCompany",
            "polarity": "P+",
            "category_list": [
                {
                    "code": "Citizenship",
                    "label": "Citizenship",
                    "polarity": "P+",
                    "abs_relevance": 1,
                    "relat_relevance": 100,
                    "sentence_list": [
                        {
                            "text": "Endesa is building the largest photovoltaic project for self-consumption in the Balearic Islands",
                            "inip": "0",
                            "endp": "95"
                        }
                    ]
                },
                {
                    "code": "Performance",
                    "label": "Performance",
                    "polarity": "P+",
                    "abs_relevance": 1,
                    "relat_relevance": 100,
                    "sentence_list": [
                        {
                            "text": "Endesa is building the largest photovoltaic project for self-consumption in the Balearic Islands",
                            "inip": "0",
                            "endp": "95"
                        }
                    ]
                }
            ]
        }
    ]
}