資料 API / DataForSEO / Content Analysis
Content Analysis – Sentiment Analysis API
Sentiment distributions for the citations of a keyword: positive_connotation_distribution (positive, negative, neutral) and sentiment_connotation_distribution (anger, happiness, love, sadness, share, fun). positive_connotation_threshold and sentiments_connotation_threshold set how confident a classification must be to count. ⚠️ Both blocks are already inside post_dataforseo_content_summary_live, which costs the same and adds domains, categories, countries and languages - prefer it unless the smaller response matters. To see the sentiment split by star rating use post_dataforseo_content_rating_distribution_live.
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keywordstring必填target keyword required field UTF-8 encoding the keywords will be converted to a lowercase format; Note: to match an exact phrase instead of a stand-alone keyword, use double quotes and backslashes; example: "keyword": "\"tesla palo alto\"" learn more about rules and limitations of keyword and keywords fields in DataForSEO APIs in this Help Center article
keyword_fieldsobject選填target keyword fields and target keywords optional field use this parameter to filter the dataset by keywords that certain fields should contain; fields you can specify: title, main_title, previous_title, snippet you can indicate several fields; Note: to match an exact phrase instead of a stand-alone keyword, use double quotes and backslashes; example: "keyword_fields": { "snippet": "\"logitech mouse\"", "main_title": "sale" }
titlestring選填main_titlestring選填previous_titlestring選填snippetstring選填page_typestring[]選填target page types optional field use this parameter to filter the dataset by page types possible values: "ecommerce", "news", "blogs", "message-boards", "organization"
internal_list_limitinteger選填maximum number of elements within internal arrays optional field you can use this field to limit the number of elements within the following arrays: top_domains text_categories page_categories countries languages default value: 1 maximum value: 20
positive_connotation_thresholdnumber選填positive connotation threshold optional field specified as the probability index threshold for positive sentiment related to the citation content if you specify this field, connotation_types object in the response will only contain data on citations with positive sentiment probability more than or equal to the specified value possible values: from 0 to 1 default value: 0.4
sentiments_connotation_thresholdnumber選填sentiment connotation threshold optional field specified as the probability index threshold for sentiment connotations related to the citation content if you specify this field, sentiment_connotations object in the response will only contain data on citations where the probability per each sentiment is more than or equal to the specified value possible values: from 0 to 1 default value: 0.4
initial_dataset_filtersarray選填initial dataset filtering parameters optional field initial filtering parameters that apply to fields in the Search endpoint you can add several filters at once (8 filters maximum) you should set a logical operator and, or between the conditions the following operators are supported: regex, not_regex, , , >, >=, =, , in, not_in, like,not_like, has, has_not, match, not_match you can use the % operator with like and not_like to match any string of zero or more characters example: ["domain","", "logitech.com"] [["domain","","logitech.com"],"and",["content_info.connotation_types.negative",">",1000]] [["domain","","logitech.com"]], "and", [["content_info.connotation_types.negative",">",1000], "or", ["content_info.text_category","has",10994]]] for more information about filters, please refer to Content Analysis API – Filters learn more about the initial dataset filters in this help center article.
rank_scalestring選填defines the scale used for calculating and displaying the rank values optional field you can use this parameter to choose whether rank values are presented on a 0–100 or 0–1000 scale possible values: one_hundred — rank values are displayed on a 0–100 scale one_thousand — rank values are displayed on a 0–1000 scale default value: one_thousand learn more about how this parameter works in this Help Center article
tagstring選填user-defined task identifier optional field the character limit is 255 you can use this parameter to identify the task and match it with the result you will find the specified tag value in the data object of the response
請求範例
curl -X POST "https://openapi.felo.ai/v1/beta/dataforseo/content_analysis/sentiment_analysis/live" \
-H "Authorization: Bearer $FELO_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"keyword": "<string>",
"keyword_fields": {},
"page_type": [
"<string>"
],
"internal_list_limit": 0,
"positive_connotation_threshold": 0,
"sentiments_connotation_threshold": 0,
"initial_dataset_filters": "<string>",
"rank_scale": "<string>"
}'回應
回應欄位
versionstring選填the current version of the API
status_codeinteger選填general status code you can find the full list of the response codes here Note: we strongly recommend designing a necessary system for handling related exceptional or error conditions
status_messagestring選填general informational message you can find the full list of general informational messages here
timestring選填execution time, seconds
costnumber選填total tasks cost, USD
tasks_countinteger選填the number of tasks in the tasks array
tasks_errorinteger選填the number of tasks in the tasks array returned with an error
tasksstring[]選填array of tasks
idstring選填task identifier unique task identifier in our system in the UUID format
status_codeinteger選填status code of the task generated by DataForSEO; can be within the following range: 10000-60000 you can find the full list of the response codes here
status_messagestring選填informational message of the task you can find the full list of general informational messages here
timestring選填execution time, seconds
costnumber選填cost of the task, USD
result_countinteger選填number of elements in the result array
pathstring[]選填URL path
dataobject選填contains the same parameters that you specified in the POST request
resultstring[]選填array of results
typestring選填type of element = ‘content_analysis_sentiment_analysis’
positive_connotation_distributionobject選填citation distribution by sentiment connotation types contains objects with citation counts and relevant data distributed by types of sentiments (sentiment polarity); possible sentiment connotation types: positive, negative, neutral
$positiveobject選填positive, negative, or neutral connotations variable can take the following values: positive, negative, neutral
typestring選填type of element = ‘content_analysis_summary’
total_countinteger選填total number of relevant results
rankinteger選填rank of all relevant URLs
top_domainsstring[]選填top relevant domains contains objects with top relevant domains and the number of citations per each domain
sentiment_connotationsobject選填sentiment connotations contains relevant sentiments (emotional reactions) and the number of citations per each sentiment; possible connotations: "anger", "happiness", "love", "sadness", "share", "fun"
connotation_typesobject選填connotation types contains types of sentiments (sentiment polarity) related to the keyword citation and citation count per each sentiment type; possible connotation types: "positive", "negative", "neutral"
text_categoriesstring[]選填text categories contains text categories and citation count in each text category to obtain a full list of available categories, refer to the Categories endpoint
page_categoriesstring[]選填page categories contains objects with page categories and citation count in each page category to obtain a full list of available categories, refer to the Categories endpoint
page_typesobject選填page types contains page types and citation count per each page type
countriesobject選填countries contains countries and citation count in each country to obtain a full list of available countries, refer to the Locations endpoint
languagesobject選填languages to obtain a full list of available languages, refer to the Languages endpoint
sentiment_connotation_distributionobject選填citation distribution by sentiment connotations contains objects with citation counts and relevant data distributed by sentiments (emotional reactions); possible sentiment connotation types: anger, happiness, love, sadness, share, fun
$angerobject選填sentiment name variable can take the following values: anger, happiness, love, sadness, share, fun
typestring選填type of element = ‘content_analysis_summary’
total_countinteger選填total number of relevant results
rankinteger選填rank of all relevant URLs
top_domainsstring[]選填top relevant domains contains objects with top relevant domains and the number of citations per each domain
sentiment_connotationsobject選填sentiment connotations contains relevant sentiments (emotional reactions) and the number of citations per each sentiment; possible connotations: "anger", "happiness", "love", "sadness", "share", "fun"
connotation_typesobject選填connotation types contains types of sentiments (sentiment polarity) related to the keyword citation and citation count per each sentiment type; possible connotation types: "positive", "negative", "neutral"
text_categoriesstring[]選填text categories contains text categories and citation count in each text category to obtain a full list of available categories, refer to the Categories endpoint
page_categoriesstring[]選填page categories contains objects with page categories and citation count in each page category to obtain a full list of available categories, refer to the Categories endpoint
page_typesobject選填page types contains page types and citation count per each page type
countriesobject選填countries contains countries and citation count in each country to obtain a full list of available countries, refer to the Locations endpoint
languagesobject選填languages to obtain a full list of available countries, refer to the Languages endpoint