building-twitter-industry-watchlist

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Original

English

🇨🇳

Translation

Chinese

Building a Twitter Industry Watchlist

构建Twitter行业观察列表

Identifies highest-signal Twitter accounts in an industry — people whose tweets consistently generate discussion, surface new information, or shape thinking in the space.

识别某一行业中信号噪音比最高的Twitter账号——这些用户的推文持续引发讨论、呈现新信息或影响行业思维。

Prerequisites

前提条件

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

已设置
```
APIFY_TOKEN
```
环境变量
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个人主页或推文URL
`twitterHandles`	数组	可选	`[]`	Twitter用户名（不含@）
`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/被封禁的用户
`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: Search for high-engagement industry tweets
- [ ] Step 2: Collect influential account handles
- [ ] Step 3: Enrich and score
- [ ] Step 4: Classify by account type
- [ ] Step 5: Deliver curated watchlist

进度:
- [ ] 步骤1：搜索高互动率的行业推文
- [ ] 步骤2：收集有影响力的账号昵称
- [ ] 步骤3：丰富信息并评分
- [ ] 步骤4：按账号类型分类
- [ ] 步骤5：交付精选观察列表

Step 1: Search Industry Conversations

步骤1：搜索行业对话

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

bash

undefined

推荐方式 — run_actor.js（自动处理等待、输出和文件保存）：

bash

undefined

Quick answer (prints table to chat)

快速输出（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格式

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格式

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~tweet-scraper" Input: { "searchTerms": ["[INDUSTRY]", "#[industry]", "[INDUSTRY] trends", "[INDUSTRY] analysis"], "maxItems": 500 }


**REST API fallback:**
```bash
curl -X POST \
  "https://api.apify.com/v2/acts/apidojo~tweet-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchTerms": ["venture capital", "#vc", "VC trends 2026"], "maxItems": 500}'

Collect authors with

likeCount + replyCount >= 10

on their industry tweets.

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

> 必须在环境变量或`.env`文件中设置`APIFY_TOKEN`。

**如果Apify MCP可用：**

工具: apify:run-actor Actor: "apidojo~tweet-scraper" 输入: { "searchTerms": ["[INDUSTRY]", "#[industry]", "[INDUSTRY] trends", "[INDUSTRY] analysis"], "maxItems": 500 }


**REST API备选方案：**
```bash
curl -X POST \
  "https://api.apify.com/v2/acts/apidojo~tweet-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchTerms": ["venture capital", "#vc", "VC trends 2026"], "maxItems": 500}'

收集那些行业推文的

点赞数 + 回复数 >= 10

的作者。

Step 2: Score Influence

步骤2：计算影响力评分

signal_score = (retweets / followers * 1000) * 0.35
             + (replies / followers * 1000) * 0.30
             + min(followers / 100000, 1) * 0.20
             + (tweeted_industry_content >= 3 in 30 days ? 1 : 0) * 0.15

Account type from bio:

FOUNDER: "founder", "CEO", "built"
INVESTOR: "partner", "VC", "investor"
ANALYST: "analyst", "researcher", "writer"
JOURNALIST: known pub or "reporter", "journalist"
PRACTITIONER: role title at company

signal_score = (retweets / followers * 1000) * 0.35
             + (replies / followers * 1000) * 0.30
             + min(followers / 100000, 1) * 0.20
             + (tweeted_industry_content >= 3 in 30 days ? 1 : 0) * 0.15

根据个人简介判断账号类型：

FOUNDER（创始人）：包含"founder"、"CEO"、"built"
INVESTOR（投资者）：包含"partner"、"VC"、"investor"
ANALYST（分析师）：包含"analyst"、"researcher"、"writer"
JOURNALIST（记者）：来自知名媒体或包含"reporter"、"journalist"
PRACTITIONER（从业者）：公司职位头衔

Step 3: Edge Cases

步骤3：特殊情况处理

Bot accounts:
```
retweetCount >> likeCount
```
→ flag if retweets > 5× likes
Ambiguous type: Use
```
PRACTITIONER
```
as default when unclear
Multiple accounts from same company: Keep the most influential one

机器人账号：
```
转发数 >> 点赞数
```
→ 若转发数 > 点赞数的5倍则标记
类型模糊：当无法明确判断时，默认归类为PRACTITIONER（从业者）
同一公司多个账号：保留最具影响力的一个

Output Format

输出格式

undefined

undefined

[INDUSTRY] Twitter Watchlist

[行业名称] Twitter观察列表

Accounts: [N] | Date: [DATE]

账号数量: [N] | 日期: [DATE]

Founders & Operators

创始人与运营者

Name	@Handle	Role	Followers	Avg Likes	Signal Score

姓名	@账号昵称	职位	粉丝数	平均点赞数	信号评分

Investors & Analysts

投资者与分析师

Name	@Handle	Role	Followers	Signal Score

姓名	@账号昵称	职位	粉丝数	信号评分

Press & Media

媒体与记者

Name	@Handle	Publication	Followers	Signal Score

姓名	@账号昵称	媒体机构	粉丝数	信号评分

How to Create Twitter List

如何创建Twitter列表

Go to Twitter → Lists → Create List → Add members by username

undefined

进入Twitter → 列表 → 创建列表 → 通过用户名添加成员

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Troubleshooting

故障排除

Results are news not insiders: Use

#[industry]

hashtag to find community members vs. general readers. Too many promotional accounts: Filter accounts where > 50% of tweets include external links. Watchlist too large: Apply score cutoff ≥ 0.60; keep ≤ 40 accounts for daily readability.

结果多为新闻而非业内人士：使用

#[industry]

话题标签来寻找社区成员，而非普通读者。 推广账号过多：过滤掉超过50%推文包含外部链接的账号。 观察列表过大：应用评分阈值≥0.60；为保证日常可读性，保留不超过40个账号。