apify-trend-analysis

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🇺🇸

Original

English

🇨🇳

Translation

Chinese

Trend Analysis

趋势分析

Discover and track emerging trends using Apify Actors to extract data from multiple platforms.

使用Apify Actors从多个平台提取数据，发现并追踪新兴趋势。

Prerequisites

前提条件

(No need to check it upfront)

```
.env
```
file with
```
APIFY_TOKEN
```
Node.js 20.6+ (for native
```
--env-file
```
support)
```
mcpc
```
CLI tool:
```
npm install -g @apify/mcpc
```

（无需预先检查）

包含
```
APIFY_TOKEN
```
的
```
.env
```
文件
Node.js 20.6+（支持原生
```
--env-file
```
功能）
```
mcpc
```
CLI工具：
```
npm install -g @apify/mcpc
```

Workflow

工作流程

Copy this checklist and track progress:

Task Progress:
- [ ] Step 1: Identify trend type (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the analysis script
- [ ] Step 5: Summarize findings

复制此检查清单并跟踪进度：

任务进度：
- [ ] 步骤1：确定趋势类型（选择Actor）
- [ ] 步骤2：通过mcpc获取Actor模式
- [ ] 步骤3：询问用户偏好（格式、文件名）
- [ ] 步骤4：运行分析脚本
- [ ] 步骤5：总结发现

Step 1: Identify Trend Type

步骤1：确定趋势类型

Select the appropriate Actor based on research needs:

User Need	Actor ID	Best For
Search trends	`apify/google-trends-scraper`	Google Trends data
Hashtag tracking	`apify/instagram-hashtag-scraper`	Hashtag content
Hashtag metrics	`apify/instagram-hashtag-stats`	Performance stats
Visual trends	`apify/instagram-post-scraper`	Post analysis
Trending discovery	`apify/instagram-search-scraper`	Search trends
Comprehensive tracking	`apify/instagram-scraper`	Full data
API-based trends	`apify/instagram-api-scraper`	API access
Engagement trends	`apify/export-instagram-comments-posts`	Comment tracking
Product trends	`apify/facebook-marketplace-scraper`	Marketplace data
Visual analysis	`apify/facebook-photos-scraper`	Photo trends
Community trends	`apify/facebook-groups-scraper`	Group monitoring
YouTube Shorts	`streamers/youtube-shorts-scraper`	Short-form trends
YouTube hashtags	`streamers/youtube-video-scraper-by-hashtag`	Hashtag videos
TikTok hashtags	`clockworks/tiktok-hashtag-scraper`	Hashtag content
Trending sounds	`clockworks/tiktok-sound-scraper`	Audio trends
TikTok ads	`clockworks/tiktok-ads-scraper`	Ad trends
Discover page	`clockworks/tiktok-discover-scraper`	Discover trends
Explore trends	`clockworks/tiktok-explore-scraper`	Explore content
Trending content	`clockworks/tiktok-trends-scraper`	Viral content

根据研究需求选择合适的Actor：

用户需求	Actor ID	适用场景
搜索趋势	`apify/google-trends-scraper`	Google Trends数据
话题标签追踪	`apify/instagram-hashtag-scraper`	话题标签内容
话题标签指标	`apify/instagram-hashtag-stats`	表现统计数据
视觉趋势	`apify/instagram-post-scraper`	帖子分析
趋势发现	`apify/instagram-search-scraper`	搜索趋势
全面追踪	`apify/instagram-scraper`	完整数据
基于API的趋势	`apify/instagram-api-scraper`	API访问
互动趋势	`apify/export-instagram-comments-posts`	评论追踪
产品趋势	`apify/facebook-marketplace-scraper`	商城数据
视觉分析	`apify/facebook-photos-scraper`	图片趋势
社区趋势	`apify/facebook-groups-scraper`	群组监控
YouTube Shorts	`streamers/youtube-shorts-scraper`	短视频趋势
YouTube话题标签	`streamers/youtube-video-scraper-by-hashtag`	话题标签视频
TikTok话题标签	`clockworks/tiktok-hashtag-scraper`	话题标签内容
热门音效	`clockworks/tiktok-sound-scraper`	音频趋势
TikTok广告	`clockworks/tiktok-ads-scraper`	广告趋势
发现页面	`clockworks/tiktok-discover-scraper`	发现页趋势
探索趋势	`clockworks/tiktok-explore-scraper`	探索页内容
热门内容	`clockworks/tiktok-trends-scraper`	爆款内容

Step 2: Fetch Actor Schema

步骤2：获取Actor模式

Fetch the Actor's input schema and details dynamically using mcpc:

bash

export $(grep APIFY_TOKEN .env | xargs) && mcpc --json mcp.apify.com --header "Authorization: Bearer $APIFY_TOKEN" tools-call fetch-actor-details actor:="ACTOR_ID" | jq -r ".content"

Replace

ACTOR_ID

with the selected Actor (e.g.,

apify/google-trends-scraper

This returns:

Actor description and README
Required and optional input parameters
Output fields (if available)

使用mcpc动态获取Actor的输入模式和详细信息：

bash

export $(grep APIFY_TOKEN .env | xargs) && mcpc --json mcp.apify.com --header "Authorization: Bearer $APIFY_TOKEN" tools-call fetch-actor-details actor:="ACTOR_ID" | jq -r ".content"

将

ACTOR_ID

替换为所选的Actor（例如：

apify/google-trends-scraper

）。

此命令将返回：

Actor描述和README
必填和可选输入参数
输出字段（如果有）

Step 3: Ask User Preferences

步骤3：询问用户偏好

Before running, ask:

Output format:
- Quick answer - Display top few results in chat (no file saved)
- CSV - Full export with all fields
- JSON - Full export in JSON format
Number of results: Based on character of use case

运行前，询问用户以下内容：

输出格式：
- 快速答复 - 在聊天中显示前几条结果（不保存文件）
- CSV - 导出包含所有字段的完整数据
- JSON - 以JSON格式导出完整数据
结果数量：根据使用场景确定

Step 4: Run the Script

步骤4：运行脚本

Quick answer (display in chat, no file):

bash

node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT'

CSV:

bash

node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT' \
  --output YYYY-MM-DD_OUTPUT_FILE.csv \
  --format csv

JSON:

bash

node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT' \
  --output YYYY-MM-DD_OUTPUT_FILE.json \
  --format json

快速答复（在聊天中显示，不保存文件）：

bash

node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT'

CSV格式：

bash

node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT' \
  --output YYYY-MM-DD_OUTPUT_FILE.csv \
  --format csv

JSON格式：

bash

node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT' \
  --output YYYY-MM-DD_OUTPUT_FILE.json \
  --format json

Step 5: Summarize Findings

步骤5：总结发现

After completion, report:

Number of results found
File location and name
Key trend insights
Suggested next steps (deeper analysis, content opportunities)

完成后，汇报以下内容：

找到的结果数量
文件位置和名称
关键趋势洞察
建议的后续步骤（深入分析、内容机会）

Error Handling

错误处理

APIFY_TOKEN not found

- Ask user to create

.env

with

APIFY_TOKEN=your_token

mcpc not found

- Ask user to install

npm install -g @apify/mcpc

Actor not found

- Check Actor ID spelling

Run FAILED

- Ask user to check Apify console link in error output

Timeout

- Reduce input size or increase

--timeout

APIFY_TOKEN not found

- 请用户创建包含

APIFY_TOKEN=your_token

的.env文件

mcpc not found

- 请用户执行

npm install -g @apify/mcpc

进行安装

Actor not found

- 检查Actor ID的拼写

Run FAILED

- 请用户查看错误输出中的Apify控制台链接

Timeout

- 减小输入规模或增加

--timeout

参数值