内容分析 – 情感分析 API
curl --request POST \
--url https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
[
{
"keyword": "logitech",
"internal_list_limit": 1
}
]
'import requests
url = "https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live"
payload = [
{
"keyword": "logitech",
"internal_list_limit": 1
}
]
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
body: JSON.stringify([{keyword: 'logitech', internal_list_limit: 1}])
};
fetch('https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "POST",
CURLOPT_POSTFIELDS => json_encode([
[
'keyword' => 'logitech',
'internal_list_limit' => 1
]
]),
CURLOPT_HTTPHEADER => [
"Authorization: Bearer <token>",
"Content-Type: application/json"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live"
payload := strings.NewReader("[\n {\n \"keyword\": \"logitech\",\n \"internal_list_limit\": 1\n }\n]")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "Bearer <token>")
req.Header.Add("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.post("https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("[\n {\n \"keyword\": \"logitech\",\n \"internal_list_limit\": 1\n }\n]")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "[\n {\n \"keyword\": \"logitech\",\n \"internal_list_limit\": 1\n }\n]"
response = http.request(request)
puts response.read_body{
"version": "<string>",
"status_code": 123,
"status_message": "<string>",
"time": "<string>",
"cost": 123,
"tasks_count": 123,
"tasks_error": 123,
"tasks": [
{
"id": "<string>",
"status_code": 123,
"status_message": "<string>",
"time": "<string>",
"cost": 123,
"result_count": 123,
"path": [
"<string>"
],
"data": {},
"result": [
{
"type": "<string>",
"positive_connotation_distribution": {
"positive": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"negative": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"neutral": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
}
},
"sentiment_connotation_distribution": {
"anger": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"happiness": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"love": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"sadness": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"share": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"fun": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
}
}
}
]
}
]
}内容分析
内容分析 – 情感分析 API
内容分析 – 情感分析 API
POST
https://api.aisa.one
/
apis
/
v1
/
dataforseo
/
content_analysis
/
sentiment_analysis
/
live
内容分析 – 情感分析 API
curl --request POST \
--url https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
[
{
"keyword": "logitech",
"internal_list_limit": 1
}
]
'import requests
url = "https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live"
payload = [
{
"keyword": "logitech",
"internal_list_limit": 1
}
]
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
body: JSON.stringify([{keyword: 'logitech', internal_list_limit: 1}])
};
fetch('https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "POST",
CURLOPT_POSTFIELDS => json_encode([
[
'keyword' => 'logitech',
'internal_list_limit' => 1
]
]),
CURLOPT_HTTPHEADER => [
"Authorization: Bearer <token>",
"Content-Type: application/json"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live"
payload := strings.NewReader("[\n {\n \"keyword\": \"logitech\",\n \"internal_list_limit\": 1\n }\n]")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "Bearer <token>")
req.Header.Add("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.post("https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("[\n {\n \"keyword\": \"logitech\",\n \"internal_list_limit\": 1\n }\n]")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "[\n {\n \"keyword\": \"logitech\",\n \"internal_list_limit\": 1\n }\n]"
response = http.request(request)
puts response.read_body{
"version": "<string>",
"status_code": 123,
"status_message": "<string>",
"time": "<string>",
"cost": 123,
"tasks_count": 123,
"tasks_error": 123,
"tasks": [
{
"id": "<string>",
"status_code": 123,
"status_message": "<string>",
"time": "<string>",
"cost": 123,
"result_count": 123,
"path": [
"<string>"
],
"data": {},
"result": [
{
"type": "<string>",
"positive_connotation_distribution": {
"positive": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"negative": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"neutral": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
}
},
"sentiment_connotation_distribution": {
"anger": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"happiness": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"love": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"sadness": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"share": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
},
"fun": {
"type": "<string>",
"total_count": 123,
"rank": 123,
"top_domains": [
{
"domain": "<string>",
"count": 123
}
],
"sentiment_connotations": {},
"connotation_types": {},
"text_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_categories": [
{
"category": [
123
],
"count": 123
}
],
"page_types": {},
"countries": {},
"languages": {}
}
}
}
]
}
]
}某关键词全部引用的情感分布：
在你的 agent 里把这个端点跑起来 →
positive_connotation_distribution（positive / negative / neutral）和 sentiment_connotation_distribution（anger / happiness / love / sadness / share / fun）。positive_connotation_threshold 和 sentiments_connotation_threshold 决定判定要多高置信度才算数。实测 5.7 KB。响应统一包在 DataForSEO 的信封里——数据在 tasks[0].result。 ⚠️ 这两个块 post_dataforseo_content_summary_live 里都有，价格相同还多给域名、类目、国家和语言——除非小响应体对你有意义，否则优先用它。要看情感按星级拆开，用 post_dataforseo_content_rating_distribution_live。
示例
curl -X POST "https://api.aisa.one/apis/v1/dataforseo/content_analysis/sentiment_analysis/live" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '[{"keyword": "...", "keyword_fields": "...", "page_type": "..."}]'
// 把整段复制给 Claude Code、Codex、Cursor 或任意 coding agent。
// 连接、授权、跑通这个例子需要的东西都在里面 ——
// 不用粘贴任何 key，浏览器里点一次 Allow 就好。
{
"operation_id": "post_dataforseo_content_sentiment_analysis_live",
"arguments": {},
"max_price_usd": 0.05
}
// ── for the agent ─────────────────────────────────────────────────────────
// Register the AIsa MCP server, then call its `use` tool with the JSON above.
// name aisa
// endpoint https://mcp.aisa.one/mcp
// transport streamable-http
// auth OAuth. The server publishes RFC 9728 metadata, so open a
// browser and the user clicks Allow once — nothing to paste.
// If AISA_API_KEY is set, send it as a bearer header instead.
// Use your own MCP mechanism, not a hand-edited config file:
// Codex codex mcp add aisa --url https://mcp.aisa.one/mcp
// Claude Code claude mcp add --transport http -s user aisa https://mcp.aisa.one/mcp
// Cursor / VS Code a "url" entry for https://mcp.aisa.one/mcp in the MCP config
// The server lists five tools over https://mcp.aisa.one/servers worth of APIs:
// search, get_details, use, batch_use, list_categories. search and
// get_details are free; use is billed per call and max_price_usd refuses
// anything above the cap before spending. This operation's full contract —
// every argument, the response shape, the price and the pitfalls — is at
// https://aisa.one/docs/zh/api-reference/dataforseo/post_dataforseo-content-analysis-sentiment-analysis-live.md
// Then run the call and show me the result.
第一次用？ 把任意 MCP 客户端指向
https://mcp.aisa.one/mcp —— Claude Code、
Codex、Cursor、VS Code 都可以。鉴权走 OAuth：客户端打开浏览器，你点一次
Allow，不需要粘贴任何 key。各客户端的具体命令和每次调用的价格见
aisa.one/zh-cn/mcp。授权
Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
请求体
application/json
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
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" }
Show child attributes
Show child attributes
target page types optional field use this parameter to filter the dataset by page types possible values: "ecommerce", "news", "blogs", "message-boards", "organization"
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 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
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 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.
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
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
示例:
[
{
"keyword": "logitech",
"internal_list_limit": 1
}
]
响应
object | null
Successful operation
API 的当前版本
general status code you can find the full list of the response codes here
general informational message you can find the full list of general informational messages here
total execution time, seconds
任务总成本（美元）
tasks 数组中的任务数量
返回错误的 tasks 数组中的任务数量
任务数组
Show child attributes
Show child attributes