Search articles by author

POST

api

authors

object

author_name

string

not_author_name

string

predefined_sources

string

sources

string

not_sources

string

lang

string

not_lang

string

countries

string

not_countries

string

from_

Option 1 · string

to_

Option 1 · string

published_date_precision

enum<string>

by_parse_date

boolean

sort_by

enum<string>

ranked_only

boolean

from_rank

integer

to_rank

integer

is_headline

boolean

is_opinion

boolean

is_paid_content

boolean

parent_url

string

all_links

string

all_domain_links

string

word_count_min

integer

word_count_max

integer

page

integer

page_size

integer

include_nlp_data

boolean

has_nlp

boolean

theme

string

not_theme

string

ner_name

string

title_sentiment_min

number

title_sentiment_max

number

content_sentiment_min

number

content_sentiment_max

number

iptc_tags

string

not_iptc_tags

string

iab_tags

string

not_iab_tags

string

custom_tags

string

Authorizations

x-api-token

string

headerrequired

API Key to authenticate requests.

To access the API, include your API key in the x-api-token header. To obtain your API key, complete the form or contact us directly.

Body

application/json

author_name

string

required

The name of the author to search for. This parameter returns exact matches only.

not_author_name

The list of author names to exclude from your search. To exclude articles by specific authors, use a comma-separated string or an array of strings.

Examples:

"John Doe, Jane Doe"
["John Doe", "Jane Doe"]

predefined_sources

Predefined top sources per country.

Format: start with the word top, followed by the number of desired sources, and then the two-letter country code ISO 3166-1 alpha-2.

Examples:

"top 100 US"
"top 33 AT"
"top 5 GB"

Multiple countries can be specified with custom numbers as a comma-separated string or an array of strings.

Examples:

"top 50 US, top 20 GB"
["top 50 US", "top 20 GB"]

sources

One or more news sources to narrow down the search. The format must be a domain URL. Subdomains, such as finance.yahoo.com, are also acceptable. To specify multiple sources, use a comma-separated string or an array of strings.

Examples:

"nytimes.com, theguardian.com"
["nytimes.com", "theguardian.com"]

not_sources

The news sources to exclude from the search. To exclude multiple sources, use a comma-separated string or an array of strings.

Examples:

"cnn.com, wsj.com"
["cnn.com", "wsj.com"]

lang

The language(s) of the search. The only accepted format is the two-letter ISO 639-1 code. To select multiple languages, use a comma-separated string or an array of strings.

Examples:

"en,es"
["en", "es"]

To learn more, see Enumerated parameters > Language.

not_lang

The language(s) to exclude from the search. The accepted format is the two-letter ISO 639-1 code. To exclude multiple languages, use a comma-separated string or an array of strings.

Examples:

"fr,de"
["fr", "de"]

To learn more, see Enumerated parameters > Language.

countries

The countries where the news publisher is located. The accepted format is the two-letter ISO 3166-1 alpha-2 code. To select multiple countries, use a comma-separated string or an array of strings.

Examples:

"US,CA"
["US", "CA"]

To learn more, see Enumerated parameters > Country.

not_countries

The publisher location countries to exclude from the search. The accepted format is the two-letter ISO 3166-1 alpha-2 code. To exclude multiple countries, use a comma-separated string or an array of strings.

Examples:

"UK,FR"
["UK", "FR"]

To learn more, see Enumerated parameters > Country.

from_

The starting point in time to search from. Accepts date-time strings in ISO 8601 format and plain text strings. The default time zone is UTC.

Formats with examples:

YYYY-mm-ddTHH:MM:SS: 2024-07-01T00:00:00
YYYY-MM-dd: 2024-07-01
YYYY/mm/dd HH:MM:SS: 2024/07/01 00:00:00
YYYY/mm/dd: 2024/07/01
English phrases: 1 day ago, today

Note: By default, applied to the publication date of the article. To use the article's parse date instead, set the by_parse_date parameter to true.

to_

The ending point in time to search up to. Accepts date-time strings in ISO 8601 format and plain text strings. The default time zone is UTC.

Formats with examples:

YYYY-mm-ddTHH:MM:SS: 2024-07-01T00:00:00
YYYY-MM-dd: 2024-07-01
YYYY/mm/dd HH:MM:SS: 2024/07/01 00:00:00
YYYY/mm/dd: 2024/07/01
English phrases: 1 day ago, today

Note: By default, applied to the publication date of the article. To use the article's parse date instead, set the by_parse_date parameter to true.

published_date_precision

enum<string>

The precision of the published date. There are three types:

full: The day and time of an article is correctly identified with the appropriate timezone.
timezone unknown: The day and time of an article is correctly identified without timezone.
date: Only the day is identified without an exact time.

Available options:

full,

timezone unknown,

date

by_parse_date

boolean

default: false

If true, the from_ and to_ parameters use article parse dates instead of published dates. Additionally, the parse_date variable is added to the output list for each article.

sort_by

enum<string>

default: relevancy

The sorting order of the results. Possible values are:

relevancy: The most relevant results first.
date: The most recently published results first.
rank: The results from the highest-ranked sources first.

Available options:

relevancy,

date,

rank

ranked_only

boolean

default: true

If true, limits the search to sources ranked in the top 1 million online websites. If false, includes unranked sources which are assigned a rank of 999999.

from_rank

integer

default: 1

The lowest boundary of the rank of a news website to filter by. Range: 1 to 999999, where a lower rank indicates a more popular source. If you set this to 100, the API includes sources ranked 100 or higher.

Required range: 1 < x < 999999

to_rank

integer

default: 999999

The highest boundary of the rank of a news website to filter by. Range: 1 to 999999, where a lower rank indicates a more popular source. If you set this to 100, the API includes sources ranked 100 or lower.

Required range: 1 < x < 999999

is_headline

boolean

If true, only returns articles that were posted on the home page of a given news domain.

is_opinion

boolean

If true, returns only opinion pieces. If false, excludes opinion-based articles and returns news only.

is_paid_content

boolean

If false, returns only articles that have publicly available complete content. Some publishers partially block content, so this setting ensures that only full articles are retrieved.

parent_url

The categorical URL(s) to filter your search. To filter your search by multiple categorical URLs, use a comma-separated string or an array of strings.

Examples:

"wsj.com/politics,wsj.com/tech"
["wsj.com/politics", "wsj.com/tech"]

all_links

The complete URL(s) mentioned in the article. For multiple URLs, use a comma-separated string or an array of strings.

Examples:

"https://aiindex.stanford.edu/report/, https://www.stateof.ai/"
["https://aiindex.stanford.edu/report/", "https://www.stateof.ai/"]

For more details, see Search by URL.

all_domain_links

The domain(s) mentioned in the article. For multiple domains, use a comma-separated string or an array of strings.

Examples:

"who.int, nih.gov"
["who.int", "nih.gov"]

For more details, see Search by URL.

word_count_min

integer

The minimum number of words an article must contain. To be used for avoiding articles with small content.

Required range: x > 0

word_count_max

integer

The maximum number of words an article can contain. To be used for avoiding articles with large content.

Required range: x > 0

page

integer

default: 1

The page number to scroll through the results. This parameter is used to paginate: scroll through results because one API response cannot return more than 1000 articles.

Required range: x > 1

page_size

integer

default: 100

The number of articles to return per page. Range: 1 to 1000.

Required range: 1 < x < 1000

include_nlp_data

boolean

default: false

If true, includes an NLP layer with each article in the response. This layer provides enhanced information such as theme classification, article summary, sentiment analysis, tags, and named entity recognition.

The NLP layer includes:

Theme: General topic of the article.
Summary: A concise overview of the article content.
Sentiment: Separate scores for title and content (range: -1 to 1).
Named entities: Identified persons (PER), organizations (ORG), locations (LOC), and miscellaneous entities (MISC).
IPTC tags: Standardized news category tags.
IAB tags: Content categories for digital advertising.

Note: The include_nlp_data parameter is only available if NLP is included in your subscription plan.

To learn more, see NLP features.

has_nlp

boolean

default: false

If true, filters the results to include only articles with an NLP layer. This allows you to focus on articles that have been processed with advanced NLP techniques.

Note: The has_nlp parameter is only available if NLP is included in your subscription plan.

To learn more, see NLP features.

theme

Filters articles based on their general topic, as determined by NLP analysis. To select multiple themes, use a comma-separated string or an array of strings.

Examples:

"Finance, Tech"
["Finance", "Tech"]

Note: The theme parameter is only available if NLP is included in your subscription plan.

To learn more, see NLP features.

Available options: Business, Economics, Entertainment, Finance, Health, Politics, Science, Sports, Tech, Crime, Financial Crime, Lifestyle, Automotive, Travel, Weather, General.

not_theme

Inverse of the theme parameter. Excludes articles based on their general topic, as determined by NLP analysis. To exclude multiple themes, use a comma-separated string or an array of strings.

Examples:

"Crime, Tech"
["Crime", "Tech"]

Note: The not_theme parameter is only available if NLP is included in your subscription plan.

To learn more, see NLP features.

ner_name

string

The name of person, organization, location, product or other named entity to search for. To specify multiple names use a comma-separated string.

Example: "Tesla, Amazon"

title_sentiment_min

number

Filters articles based on the minimum sentiment score of their titles.

Range is -1.0 to 1.0, where:

Negative values indicate negative sentiment.
Positive values indicate positive sentiment.
Values close to 0 indicate neutral sentiment.

Note: The title_sentiment_min parameter is only available if NLP is included in your subscription plan.

To learn more, see NLP features.

Required range: -1 < x < 1

title_sentiment_max

number

Filters articles based on the maximum sentiment score of their titles.

Range is -1.0 to 1.0, where:

Negative values indicate negative sentiment.
Positive values indicate positive sentiment.
Values close to 0 indicate neutral sentiment.

Note: The title_sentiment_max parameter is only available if NLP is included in your subscription plan.

To learn more, see NLP features.

Required range: -1 < x < 1

content_sentiment_min

number

Filters articles based on the minimum sentiment score of their content.

Range is -1.0 to 1.0, where:

Negative values indicate negative sentiment.
Positive values indicate positive sentiment.
Values close to 0 indicate neutral sentiment.

Note: The content_sentiment_min parameter is only available if NLP is included in your subscription plan.

To learn more, see NLP features.

Required range: -1 < x < 1

content_sentiment_max

number

Filters articles based on the maximum sentiment score of their content.

Range is -1.0 to 1.0, where:

Negative values indicate negative sentiment.
Positive values indicate positive sentiment.
Values close to 0 indicate neutral sentiment.

Note: The content_sentiment_max parameter is only available if NLP is included in your subscription plan.

To learn more, see NLP features.

Required range: -1 < x < 1

iptc_tags

Filters articles based on IPTC (International Press Telecommunications Council) media topic tags. To specify multiple IPTC tags, use a comma-separated string or an array of strings.

Examples:

"20000199, 20000209"
["20000199", "20000209"]

Note: The iptc_tags parameter is only available if tags are included in your subscription plan.

To learn more, see IPTC Media Topic NewsCodes.

not_iptc_tags

Inverse of the iptc_tags parameter. Excludes articles based on IPTC (International Press Telecommunications Council) media topic tags. To specify multiple IPTC tags to exclude, use a comma-separated string or an array of strings.

Examples:

"20000205, 20000209"
["20000205", "20000209"]

Note: The not_iptc_tags parameter is only available if tags are included in your subscription plan.

To learn more, see IPTC Media Topic NewsCodes.

iab_tags

Filters articles based on IAB (Interactive Advertising Bureau) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories, use a comma-separated string or an array of strings.

Examples:

"Business, Events"
["Business", "Events"]

Note: The iab_tags parameter is only available if tags are included in your subscription plan.

To learn more, see the IAB Content taxonomy.

not_iab_tags

Inverse of the iab_tags parameter. Excludes articles based on IAB (Interactive Advertising Bureau) content categories. These tags provide a standardized taxonomy for digital advertising content categorization. To specify multiple IAB categories to exclude, use a comma-separated string or an array of strings.

Examples:

"Agriculture, Metals"
["Agriculture", "Metals"]

Note: The not_iab_tags parameter is only available if tags are included in your subscription plan.

To learn more, see the IAB Content taxonomy.

custom_tags

Filters articles based on custom taxonomy tags specific to your organization. Each taxonomy is a custom-built classification system tailored to your specific needs and is accessible only with your API key.

To specify taxonomy and its tags, use the following pattern:

"custom_tags.taxonomy": "Tag1,Tag2,Tag3",

where taxonomy is your taxonomy name and Tag1,Tag2,Tag3 are specific tags. For multiple tags, use a comma-separated string or an array of strings.

Examples:

"custom_tags.my_taxonomy": "Tag1,Tag2,Tag3"
"custom_tags.my_taxonomy": ["Tag1", "Tag2", "Tag3"]

To learn more, see the Custom tags.

Response

200 - application/json

The response model for a successful Authors search request.

Response field behavior:

Required fields are guaranteed to be present and non-null.
Optional fields may be null/undefined if the data couldn't be extracted during processing.
To access article properties in the articles response array, use array index notation. For example, articles[n].title, where n is the zero-based index of the article object (0, 1, 2, etc.).
The nlp property within the article object articles[n].nlp is only available with NLP-enabled subscription plans.

status

string

default: okrequired

The status of the response.

total_hits

integer

required

The total number of articles matching the search criteria.

page

integer

required

The current page number of the results.

total_pages

integer

required

The total number of pages available for the given search criteria.

page_size

integer

required

The number of articles per page.

articles

object[]

required

A list of articles matching the search criteria.

articles.title

string

required

The title of the article.

articles.author

string

The primary author of the article.

articles.authors

A list of authors of the article.

articles.journalists

A list of journalists associated with the article.

articles.published_date

string

The date the article was published.

articles.published_date_precision

string

The precision of the published date.

articles.updated_date

string

The date the article was last updated.

articles.updated_date_precision

string

The precision of the updated date.

articles.parse_date

string

The date the article was parsed.

articles.link

string

required

The URL link to the article.

articles.domain_url

string

required

The domain URL of the article.

articles.full_domain_url

string

required

The full domain URL of the article.

articles.name_source

string

The name of the source where the article was published.

articles.is_headline

string

Indicates if the article is a headline.

articles.paid_content

boolean

Indicates if the article is paid content.

articles.extraction_data

string

required

The data extracted from the article.

articles.country

string

The country where the article was published.

articles.rights

string

The rights information for the article.

articles.rank

integer

required

The rank of the article's source.

articles.media

string

The media associated with the article.

articles.language

string

The language in which the article is written.

articles.description

string

A brief description of the article.

articles.content

string

required

The content of the article.

articles.word_count

integer

default: 0

The word count of the article.

articles.is_opinion

boolean

Indicates if the article is an opinion piece.

articles.twitter_account

string

The Twitter account associated with the article.

articles.all_links

A list of all URLs mentioned in the article.

articles.all_domain_links

A list of all domain URLs mentioned in the article.

articles.nlp

object

Natural Language Processing data for the article.

articles.nlp.theme

string[]

The themes or categories identified in the article.

articles.nlp.summary

string

A brief AI-generated summary of the article content.

articles.nlp.sentiment

object

Sentiment scores for the article's title and content.

articles.nlp.new_embedding

number[]

A dense 1024-dimensional vector representation of the article content, generated using the multilingual-e5-large model.

Note: The new_embedding field is only available in the v3_local_news_nlp_embeddings subscription plan.

articles.nlp.ner_PER

object[]

Named Entity Recognition for person entities (individuals' names).

articles.nlp.ner_ORG

object[]

Named Entity Recognition for organization entities (company names, institutions).

articles.nlp.ner_MISC

object[]

Named Entity Recognition for miscellaneous entities (events, nationalities, products).

articles.nlp.ner_LOC

object[]

Named Entity Recognition for location entities (cities, countries, geographic features).

articles.nlp.iptc_tags_name

string[]

IPTC media topic taxonomy paths identified in the article content. Each path represents a hierarchical category following the IPTC standard.

articles.nlp.iptc_tags_id

string[]

IPTC media topic numeric codes identified in the article content. These codes correspond to the standardized IPTC media topic taxonomy.

articles.nlp.iab_tags_name

string[]

IAB content taxonomy paths identified in the article content. Each path represents a hierarchical category following the IAB content standard.

articles.id

string

required

The unique identifier for the article.

articles.score

number

required

The relevance score of the article.

articles.custom_tags

object

An object that contains custom tags associated with an article, where each key is a taxonomy name, and the value is an array of tags.

articles.additional_domain_info

object

Additional information about the domain of the article.

user_input

object

required

The user input parameters for the search.

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Overview

Endpoints

Libraries

Search articles by author

Authorizations

Body

Response