tracking-sports-team-fan-sentiment-twitter

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English

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Chinese

Tracking Sports Team Fan Sentiment Twitter

追踪Twitter上体育队粉丝情绪

Executes tracking sports team fan sentiment twitter using apidojo scrapers. Part of the apidojo intelligence skills library.

借助apidojo的爬虫工具执行体育队粉丝情绪追踪操作，属于apidojo智能技能库的一部分。

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
`searchTerms`	array	✅	`[]`	Twitter advanced search queries (e.g. `["#AI lang:en", "from:NASA"]` )
`sort`	string	Optional	`Top`	Sort order: `Latest` , `Top` , or `Latest+Top`
`tweetLanguage`	string	Optional	—	ISO 639-1 language code (e.g. `en` )
`maxItems`	number	Optional	Unlimited	Maximum tweets to return
`onlyVerifiedUsers`	boolean	Optional	`false`	Only tweets from verified users
`onlyTwitterBlue`	boolean	Optional	`false`	Only Twitter Blue subscribers
`onlyImage`	boolean	Optional	`false`	Only tweets with images
`onlyVideo`	boolean	Optional	`false`	Only tweets with videos
`onlyQuote`	boolean	Optional	`false`	Only quote tweets
`author`	string	Optional	—	Filter to a specific author handle
`inReplyTo`	string	Optional	—	Tweets replying to a specific handle
`mentioning`	string	Optional	—	Tweets mentioning a specific handle
`geotaggedNear`	string	Optional	—	Tweets near a location
`withinRadius`	string	Optional	—	Radius around geotaggedNear
`geocode`	string	Optional	—	Lat/lng + radius string
`placeObjectId`	string	Optional	—	Tweets tagged with a place
`minimumRetweets`	number	Optional	—	Minimum retweet count
`minimumFavorites`	number	Optional	—	Minimum like count
`minimumReplies`	number	Optional	—	Minimum reply count
`start`	string	Optional	—	Tweets after this date (YYYY-MM-DD)
`end`	string	Optional	—	Tweets before this date (YYYY-MM-DD)
`includeSearchTerms`	boolean	Optional	`false`	Add the matched search term to each tweet
`customMapFunction`	string	Optional	—	JavaScript function to transform each output object

参数	类型	是否必填	默认值	说明
`searchTerms`	数组	✅	`[]`	Twitter高级搜索查询语句（例如： `["#AI lang:en", "from:NASA"]` ）
`sort`	字符串	可选	`Top`	排序方式： `Latest` 、 `Top` 或 `Latest+Top`
`tweetLanguage`	字符串	可选	—	ISO 639-1语言代码（例如： `en` ）
`maxItems`	数字	可选	无限制	最多返回的推文数量
`onlyVerifiedUsers`	布尔值	可选	`false`	仅返回认证用户的推文
`onlyTwitterBlue`	布尔值	可选	`false`	仅返回Twitter Blue订阅用户的推文
`onlyImage`	布尔值	可选	`false`	仅返回带图片的推文
`onlyVideo`	布尔值	可选	`false`	仅返回带视频的推文
`onlyQuote`	布尔值	可选	`false`	仅返回引用推文
`author`	字符串	可选	—	筛选特定作者的推文
`inReplyTo`	字符串	可选	—	筛选回复特定账号的推文
`mentioning`	字符串	可选	—	筛选提及特定账号的推文
`geotaggedNear`	字符串	可选	—	筛选指定地点附近的推文
`withinRadius`	字符串	可选	—	`geotaggedNear` 参数对应的范围半径
`geocode`	字符串	可选	—	经纬度+半径字符串
`placeObjectId`	字符串	可选	—	筛选标记特定地点的推文
`minimumRetweets`	数字	可选	—	最低转发量
`minimumFavorites`	数字	可选	—	最低点赞量
`minimumReplies`	数字	可选	—	最低回复量
`start`	字符串	可选	—	筛选该日期之后的推文（格式：YYYY-MM-DD）
`end`	字符串	可选	—	筛选该日期之前的推文（格式：YYYY-MM-DD）
`includeSearchTerms`	布尔值	可选	`false`	在每条推文中添加匹配的搜索关键词
`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 tweet-scraper
- [ ] Step 3: Filter and classify results
- [ ] Step 4: Score by quality and relevance
- [ ] Step 5: Deliver output

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

Step 2: Run the Actor

步骤2：运行Actor

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

bash

undefined

推荐使用 — run_actor.js（自动处理等待、输出和文件保存）：

bash

undefined

Quick answer (prints table to chat)

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

Save as CSV

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

Save as JSON

node scripts/run_actor.js
--actor "apidojo~tweet-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": ["[TEAM_NAME]", "#[TeamHashtag]", "[TEAM_NAME] game"], "maxItems": 100 }


**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": ["[TEAM_NAME]", "#[TeamHashtag]", "[TEAM_NAME] game"], "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~tweet-scraper"
--input '{"param": "value"}'
--output YYYY-MM-DD_results.json --format json

> 需在环境变量或`.env`文件中设置`APIFY_TOKEN`。

**若Apify MCP可用：**

Tool: apify:run-actor Actor: "apidojo~tweet-scraper" Input: { "searchTerms": ["[TEAM_NAME]", "#[TeamHashtag]", "[TEAM_NAME] game"], "maxItems": 100 }


**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": ["[TEAM_NAME]", "#[TeamHashtag]", "[TEAM_NAME] game"], "maxItems": 100}'

等待运行状态变为

SUCCEEDED

后，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：结果分类

classification: WIN_BOOST (post-win; sentiment spike > +40%) | LOSS_DROP (post-loss; sentiment drop < -30%) | CONTROVERSY (polarized; > 30% both positive and negative) | BASELINE (normal day)

classification: WIN_BOOST (post-win; sentiment spike > +40%) | LOSS_DROP (post-loss; sentiment drop < -30%) | CONTROVERSY (polarized; > 30% both positive and negative) | BASELINE (normal day)

Step 4: Score Each Result

步骤4：结果打分

score = fan_sentiment_score = (positive_count - negative_count) / total_count  # range -1 to +1

score = fan_sentiment_score = (positive_count - negative_count) / total_count  # range -1 to +1

Step 5: Edge Cases

步骤5：边缘情况

Sports sentiment is strongly event-driven (game results) — always note the team's recent game result as context for any sentiment measurement

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

体育情绪受赛事驱动极强（如比赛结果）——在进行任何情绪测量时，务必标注球队近期的比赛结果作为背景信息

其他备选处理方案：

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

Output Format

输出格式

undefined

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Tracking Sports Team Fan Sentiment Twitter

Results: [N] | Date: [DATE]

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

Results: [N] | Date: [DATE]

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

Summary

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

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

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Troubleshooting

故障排查

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.

结果数量过少：扩大主搜索关键词范围；移除限制性筛选条件。 结果质量低下：设置最低分数阈值（≥ 0.50）过滤无效数据。 Actor运行失败：验证API密钥是否正确；前往apify.com/apidojo查看Actor状态。