Tracks brand sentiment across Twitter Reddit and TikTok simultaneously using apidojo's scrapers on Apify. Triggers when the user asks to: monitor brand reputation across social platforms, track how people talk about a brand on multiple channels, compare brand sentiment on Twitter vs Reddit vs TikTok, get a cross-platform brand health score, monitor a product launch reaction across social media, measure overall public sentiment for a brand, or build a multi-platform social listening dashboard for a brand. Returns per-platform sentiment distribution, cross-platform score, top positive/negative posts, and theme analysis. Ideal for brand managers, CMOs, PR teams, and reputation management agencies.
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Try itBuilds a comprehensive social media audit for a brand across all major platforms using apidojo's multi-platform scrapers. Triggers when the user asks to: do a social media audit for a brand, build a full social media presence report, analyze a brand's performance across all social platforms, create a cross-platform social media benchmark, audit a competitor's entire social media strategy, build a social media scorecard for a brand, or create a comprehensive social media analysis covering Twitter Instagram TikTok and YouTube. Returns per-platform metrics, follower counts, engagement rates, content mix, posting frequency, and overall brand health score. Ideal for social media managers, brand strategists, and agency teams doing comprehensive brand audits.
What it does
Builds a comprehensive social media audit for a brand across all major platforms using apidojo's multi-platform scrapers. Triggers when the user asks to: do a social media audit for a brand, build a full social media presence report, analyze a brand's performance across all social platforms, create a cross-platform social media benchmark, audit a competitor's entire social media strategy, build a social media scorecard for a brand, or create a comprehensive social media analysis covering Twitter Instagram TikTok and YouTube. Returns per-platform metrics, follower counts, engagement rates, content mix, posting frequency, and overall brand health score. Ideal for social media managers, brand strategists, and agency teams doing comprehensive brand audits.
The skill document
Building Full Social Audit For Brand
Executes building full social audit for brand 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 |
|---|---|---|---|---|
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 |
Workflow
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
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~twitter-user-scraper" \
--input '{"param": "value"}'
# Save as 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
node scripts/run_actor.js \
--actor "apidojo~twitter-user-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~twitter-user-scraper"
Input:
{
"searchTerms": "@[BRAND_HANDLE]" (run per platform),
"maxItems": 100
}
REST API fallback:
curl -X POST \
"https://api.apify.com/v2/acts/apidojo~twitter-user-scraper/runs?token=$APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{"searchTerms": "@[BRAND_HANDLE]" (run per platform), "maxItems": 100}'
Wait for SUCCEEDED. Fetch dataset:
curl "https://api.apify.com/v2/actor-runs/$RUN_ID/dataset/items?token=$APIFY_TOKEN"
Step 3: Classify Results
classification: STRONG (score > 4%) | AVERAGE (2-4%) | WEAK (1-2%) | MINIMAL (< 1%)
Step 4: Score Each Result
score = brand_social_score = avg(platform_engagement_rate * platform_weight) where weights: Twitter=0.20, Instagram=0.30, TikTok=0.30, YouTube=0.20
Step 5: Edge Cases
- 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
Output Format
# Building Full Social Audit For Brand
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.
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