monitoring-trending-topics-twitter-by-niche
Monitors trending topics and conversations in a specific niche on Twitter using apidojo's Twitter Search scraper. Triggers when the user asks to: monitor trending topics in a niche on Twitter, track what's being discussed in an industry on X right now, find emerging conversations in a sector on Twitter, see what topics are trending in a specific community, track real-time buzz around a business topic on Twitter, or identify breaking trends before they hit mainstream media. Returns trending topics, tweet velocity, engagement signals, and top voices in the trend. Ideal for social media managers, PR teams, and real-time content strategists.
- Installs
- 770
- Last 24h
- +13
- Trending rank
- #7708
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/apidojo-io/apidojo-skills --skill monitoring-trending-topics-twitter-by-niche- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads monitoring-trending-topics-twitter-by-niche automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Monitoring Trending Topics Twitter By Niche
Executes monitoring trending topics twitter by niche using apidojo scrapers. Part of the apidojo intelligence skills library.
Prerequisites
APIFY_TOKENenvironment variable set- Optional: Apify MCP server installed
Inputs
| 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 |
Workflow
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
Recommended — run_actor.js (handles waiting, output, and file saving automatically):
# 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_TOKENmust be set in environment or.envfile.
If Apify MCP is available:
Tool: apify:run-actor
Actor: "apidojo~tweet-scraper"
Input:
{
"searchTerms": ["[NICHE]", "#[niche]trending", "[NICHE] breaking"],
"maxItems": 100
}
REST API fallback:
curl -X POST \
"https://api.apify.com/v2/acts/apidojo~tweet-scraper/runs?token=$APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{"searchTerms": ["[NICHE]", "#[niche]trending", "[NICHE] breaking"], "maxItems": 100}'
Wait for SUCCEEDED. Fetch dataset:
curl "https://api.apify.com/v2/actor-runs/$RUN_ID/dataset/items?token=$APIFY_TOKEN"
Step 3: Classify Results
classification: BREAKING (velocity > 3×) | RISING (1.5-3×) | STEADY (0.8-1.5×) | DECLINING (< 0.8×)
Step 4: Score Each Result
score = trend_velocity = count(tweets_in_last_24h) / count(tweets_in_prior_24h)
Step 5: Edge Cases
- Distinguish trending within the niche from general Twitter trending — verify the topic is genuinely relevant to the niche by checking co-occurring keywords
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
Output Format
# Monitoring Trending Topics Twitter By Niche
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]
Troubleshooting
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.
FAQ
What does the monitoring-trending-topics-twitter-by-niche skill do?
Monitors trending topics and conversations in a specific niche on Twitter using apidojo's Twitter Search scraper. Triggers when the user asks to: monitor trending topics in a niche on Twitter, track what's being discussed in an industry on X right now, find emerging conversations in a sector on Twitter, see what topics are trending in a specific community, track real-time buzz around a business topic on Twitter, or identify breaking trends before they hit mainstream media. Returns trending topics, tweet velocity, engagement signals, and top voices in the trend. Ideal for social media managers, PR teams, and real-time content strategists.
How do I install monitoring-trending-topics-twitter-by-niche?
Run npx skills add https://github.com/apidojo-io/apidojo-skills --skill monitoring-trending-topics-twitter-by-niche in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/monitoring-trending-topics-twitter-by-niche/ (personal) or .claude/skills/monitoring-trending-topics-twitter-by-niche/ (project).
Which AI agents can use monitoring-trending-topics-twitter-by-niche?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is monitoring-trending-topics-twitter-by-niche safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains monitoring-trending-topics-twitter-by-niche?
It is published by apidojo-io in apidojo-io/apidojo-skills. It has 770 recorded installs.
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