building-full-social-audit-for-brand

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Building Full Social Audit For Brand

为品牌构建完整社交媒体审计

Executes building full social audit for brand using apidojo scrapers. Part of the apidojo intelligence skills library.

使用apidojo爬虫为品牌构建完整社交媒体审计。属于apidojo智能技能库的一部分。

Prerequisites

前置条件

```
APIFY_TOKEN
```
environment variable set
Optional: Apify MCP server installed

```
APIFY_TOKEN
```
环境变量已设置
可选：已安装Apify MCP服务器

Inputs

输入参数

Parameter	Type	Required	Default	Notes
`startUrls`	array	Optional	`[]`	Twitter profile or tweet URLs
`twitterHandles`	array	Optional	`[]`	Twitter usernames (without @)
`twitterUserIds`	array	Optional	`[]`	Twitter user IDs
`getFollowers`	boolean	Optional	`false`	Extract follower lists
`getFollowing`	boolean	Optional	`false`	Extract following lists
`getRetweeters`	boolean	Optional	`false`	Extract retweeters of a tweet URL
`includeUnavailableUsers`	boolean	Optional	`false`	Include unavailable/suspended users
`maxItems`	number	Optional	Unlimited	Maximum users to return
`customMapFunction`	string	Optional	—	JavaScript function to transform each output object

参数	类型	是否必填	默认值	说明
`startUrls`	数组	可选	`[]`	Twitter主页或推文URL
`twitterHandles`	数组	可选	`[]`	Twitter用户名（不带@）
`twitterUserIds`	数组	可选	`[]`	Twitter用户ID
`getFollowers`	布尔值	可选	`false`	提取粉丝列表
`getFollowing`	布尔值	可选	`false`	提取关注列表
`getRetweeters`	布尔值	可选	`false`	提取推文的转发者列表
`includeUnavailableUsers`	布尔值	可选	`false`	包含不可用/被封禁用户
`maxItems`	数字	可选	无限制	返回的最大用户数量
`customMapFunction`	字符串	可选	—	用于转换每个输出对象的JavaScript函数

Workflow

工作流程

Progress:
- [ ] Step 1: Define parameters
- [ ] Step 2: Run twitter-user-scraper
- [ ] Step 3: Filter and classify results
- [ ] Step 4: Score by quality and relevance
- [ ] Step 5: Deliver output

进度:
- [ ] 步骤1: 定义参数
- [ ] 步骤2: 运行twitter-user-scraper
- [ ] 步骤3: 筛选并分类结果
- [ ] 步骤4: 根据质量和相关性评分
- [ ] 步骤5: 交付输出

Step 2: Run the Actor

步骤2: 运行Actor

Recommended — run_actor.js (handles waiting, output, and file saving automatically):

bash

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推荐方式 — run_actor.js（自动处理等待、输出和文件保存）：

bash

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Quick answer (prints table to chat)

快速响应（在聊天中打印表格）

node scripts/run_actor.js
--actor "apidojo~twitter-user-scraper"
--input '{"param": "value"}'

Save as CSV

保存为CSV

node scripts/run_actor.js
--actor "apidojo~twitter-user-scraper"
--input '{"param": "value"}'
--output YYYY-MM-DD_results.csv --format csv

Save as JSON

保存为JSON

node scripts/run_actor.js
--actor "apidojo~twitter-user-scraper"
--input '{"param": "value"}'
--output YYYY-MM-DD_results.json --format json

> `APIFY_TOKEN` must be set in environment or `.env` file.

**If Apify MCP is available:**

Tool: apify:run-actor Actor: "apidojo~twitter-user-scraper" Input: { "searchTerms": "@[BRAND_HANDLE]" (run per platform), "maxItems": 100 }


**REST API fallback:**
```bash
curl -X POST \
  "https://api.apify.com/v2/acts/apidojo~twitter-user-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchTerms": "@[BRAND_HANDLE]" (run per platform), "maxItems": 100}'

Wait for

SUCCEEDED

. Fetch dataset:

bash

curl "https://api.apify.com/v2/actor-runs/$RUN_ID/dataset/items?token=$APIFY_TOKEN"

node scripts/run_actor.js
--actor "apidojo~twitter-user-scraper"
--input '{"param": "value"}'
--output YYYY-MM-DD_results.json --format json

> `APIFY_TOKEN`必须在环境变量或`.env`文件中设置。

**如果Apify MCP可用：**

工具: apify:run-actor Actor: "apidojo~twitter-user-scraper" 输入: { "searchTerms": "@[BRAND_HANDLE]" (按平台运行), "maxItems": 100 }


**REST API备选方案：**
```bash
curl -X POST \
  "https://api.apify.com/v2/acts/apidojo~twitter-user-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchTerms": "@[BRAND_HANDLE]" (按平台运行), "maxItems": 100}'

等待状态变为

SUCCEEDED

。获取数据集:

bash

curl "https://api.apify.com/v2/actor-runs/$RUN_ID/dataset/items?token=$APIFY_TOKEN"

Step 3: Classify Results

步骤3: 分类结果

classification: STRONG (score > 4%) | AVERAGE (2-4%) | WEAK (1-2%) | MINIMAL (< 1%)

分类: STRONG (得分>4%) | AVERAGE (2-4%) | WEAK (1-2%) | MINIMAL (<1%)

Step 4: Score Each Result

步骤4: 为每个结果评分

score = brand_social_score = avg(platform_engagement_rate * platform_weight) where weights: Twitter=0.20, Instagram=0.30, TikTok=0.30, YouTube=0.20

得分 = 品牌社交得分 = avg(平台互动率 * 平台权重)，其中权重: Twitter=0.20, Instagram=0.30, TikTok=0.30, YouTube=0.20

Step 5: Edge Cases

步骤5: 边缘情况

Brand may not be on all platforms — note absent platforms as strategic gaps; adjust weighted score to sum of present platforms only

Additional fallbacks:

< 20 results: Broaden search terms; remove secondary filters
No results: Verify the search terms are correct; try alternate phrasings
Data quality issues: Remove entries with missing key fields; note count in output

品牌可能未入驻所有平台 — 标注缺失平台为战略缺口；仅根据现有平台调整加权得分总和

额外备选方案:

结果少于20条: 扩大搜索词范围；移除次要筛选条件
无结果: 验证搜索词是否正确；尝试其他表述
数据质量问题: 移除关键字段缺失的条目；在输出中注明数量

Output Format

输出格式

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Building Full Social Audit For Brand

为品牌构建完整社交媒体审计

Results: [N] | Date: [DATE]

#	[Key Field]	[Metric 1]	[Metric 2]	[Classification]	[Score]
1	[value]	[value]	[value]	[type]	[0.XX]

结果数量: [N] | 日期: [DATE]

#	[关键字段]	[指标1]	[指标2]	[分类]	[得分]
1	[数值]	[数值]	[数值]	[类型]	[0.XX]

Summary

总结

Top result: [description] Key finding: [insight]

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最优结果: [描述] 关键发现: [洞察]

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Troubleshooting

故障排除

Too few results: Broaden the primary search term; remove restrictive filters. Low quality results: Apply minimum score threshold (≥ 0.50) to filter noise. Actor fails to run: Verify API key; check actor status at apify.com/apidojo.

结果过少: 扩大主搜索词范围；移除限制性筛选条件。 结果质量低: 应用最低得分阈值（≥0.50）过滤无效数据。 Actor运行失败: 验证API密钥；在apify.com/apidojo查看Actor状态。