apidojo-io/apidojo-skills

analyzing-competitor-twitter-profile-content

Extracts and analyzes tweet history from competitor or brand Twitter profiles using apidojo's Twitter Profile Scraper on Apify.

Quelltext ansehen

Verwendung

  1. Installationsbefehl kopieren und das Quellpaket vor der Installation in der eigenen Agentenumgebung prüfen.
  2. Benötigte Werkzeuge, Zugangsdaten und Hosts im Original prüfen.
  3. Eingabe und gewünschtes Ergebnis beschreiben und die Ausgabe mit den Quellen abgleichen.
npx skills add https://github.com/apidojo-io/apidojo-skills --skill analyzing-competitor-twitter-profile-content

Vor dem Start

  • Die Installation umfasst weder Modellabo noch API-Kontingent oder Dateizugriffsrechte.
  • Sterne und Installationen zeigen Aktivität, keine unabhängige Qualitäts- oder Sicherheitsprüfung.
Originales Skill-Dokument

Aus dem Quell-Repository gerendert; Überschriften, Beispiele, Code, Tabellen, Links und Bilder bleiben erhalten.

Analyzing Competitor Twitter Profile Content


Inputs

ParameterTypeRequiredDefaultNotes
startUrlsarrayOptional[]Twitter profile URLs (x.com or twitter.com formats)
twitterHandlesarrayOptional[]Twitter usernames (without @)
startstringOptional—Tweets after this date (YYYY-MM-DD or YYYY-MM-DDHH:MM:SSUTC)
endstringOptional—Tweets before this date (YYYY-MM-DD or YYYY-MM-DDHH:MM:SSUTC)
includeNativeRetweetsbooleanOptionalfalseInclude native retweets in results
onlyImagesbooleanOptionalfalseOnly tweets containing images
getRepliesbooleanOptionalfalseInclude tweet replies
minReplyCountnumberOptional—Minimum reply count threshold
getAboutDatabooleanOptionalfalseFetch full profile about data
maxItemsnumberOptionalUnlimitedMaximum tweets to return
customMapFunctionstringOptional—JavaScript function to transform each output object

How to Run

Using run_actor.js (recommended)

bash
# Quick answer (table)
node scripts/run_actor.js --actor "apidojo~twitter-profile-scraper" --input '{"twitterHandles": ["competitor_handle"], "maxItems": 100}'

# Save as CSV
node scripts/run_actor.js --actor "apidojo~twitter-profile-scraper" --input '{"twitterHandles": ["competitor_handle"], "maxItems": 100}' --output results.csv --format csv

# Save as JSON
node scripts/run_actor.js --actor "apidojo~twitter-profile-scraper" --input '{"twitterHandles": ["competitor_handle"], "maxItems": 100}' --output results.json --format json

REST API fallback

bash
curl -X POST "https://api.apify.com/v2/acts/apidojo~twitter-profile-scraper/runs" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"twitterHandles": ["competitor_handle"], "maxItems": 100}'

If Apify MCP is available: Use the Apify MCP call_actor tool with actor apidojo~twitter-profile-scraper and the input above.


Scoring & Ranking

Score each tweet for competitive intelligence value:

  • engagement_total = likeCount + retweetCount + replyCount + quoteCount → normalized 0-1 (cap at 10K), weight 0.50
  • viewCount → normalized 0-1 (cap at 500K), weight 0.30
  • has_media (contains image or video) → 0 or 1, weight 0.20
python
score = 0.50 * min(engagement_total / 10000, 1.0) + 0.30 * min(viewCount / 500000, 1.0) + 0.20 * int(has_media)

Classification

ScoreTierLabel
≥ 0.70AHIGHIMPACTTWEET
0.40–0.69BNOTABLE_TWEET
< 0.40CLOW_ENGAGEMENT

Edge Cases

  • Private account: Returns 0 tweets. Check if competitor locked their account.
  • Minimum 40 tweets: First 40 are included at base pricing. For more, cost is $0.0004/tweet.
  • Retweets included: Results include RTs. Filter by checking if text starts with "RT @".
  • Date range + few results: Some accounts tweet rarely — widen date range or remove filter.
  • Multiple competitors: Run for each handle separately and combine datasets.

Verwandte Aufgaben

aus demselben Repository

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