LinkedIn Profile Reactions Scraper | Activity & Posts

Collect reactions made by LinkedIn profiles with available post content, media and engagement. Filter dates and export structured activity data to JSON or CSV.

Key benefits

• No customer cookies or login required for supported public-data operations.
• Structured records for research, engagement analysis and data workflows.
• Bounded pagination, request and spending controls.
• Export JSON, CSV or Excel from the run dataset.

How it works

1. Add your targets using the Input tab or JSON below.
2. Set a small result limit and maximum run spending.
3. Start the actor and inspect Output and the run SUMMARY.
4. Export results or use the Apify API to retrieve the dataset.

Collect reaction activity by each target profile, retaining available post details, media and engagement. No main-profile enrichment option is exposed by this actor.

Example input

{
  "profiles": [
    "https://www.linkedin.com/in/satyanadella"
  ],
  "maxItems": 5
}

Input options

Field	Meaning
profiles	LinkedIn profile URLs or identifiers whose activity should be collected.
maxItems	Maximum returned records per input target. Zero continues within page, request and spending limits.
postedLimit	Keep available records within this age window. Results depend on source availability.

A zero result limit means available results within page, request, spending and trial caps; it is not an unlimited-volume guarantee. Free-plan trial runs are restricted to two source requests and two primary records. Additional requests may be needed for reply previews and enrichment.

Data and output example

Fields retain their nested structure and can be absent or empty. The shortened example below uses fictional values to illustrate structure. It is not a real result or a promise of complete fields.

[
  {
    "id": "example-reaction",
    "reactionType": "LIKE",
    "actor": {
      "name": "Example Author"
    },
    "linkedinUrl": "https://www.linkedin.com/feed/update/urn:li:activity:7348831781036400646/"
  }
]

CrawlKite pricing

The actor's Pricing tab is authoritative. Enrichment and enabled engagement have separate billing events. See each event's unit below; request counts and returned item counts are different.

Billing event / unit	Free	Starter	Scale	Business
reaction / 1,000	$1.8	$1.8	$1.575	$1.35

Price comparison

Event / unit	Plan	HarvestAPI	CrawlKite	Lower by
reaction / 1,000	Free	$2	$1.8	10%
reaction / 1,000	Starter	$2	$1.8	10%
reaction / 1,000	Scale	$1.75	$1.575	10%
reaction / 1,000	Business	$1.5	$1.35	10%

Checked 2026-11-02 against the corresponding public actor pricing. The comparison covers the four plans listed and individual billing events; total costs depend on results and selected options. Higher-plan rates currently follow our Business rates. This is a price comparison, not a guarantee of identical coverage, speed or data values.

API example

Keep your Apify token in an environment variable.

curl -X POST 'https://api.apify.com/v2/acts/crawlkite~linkedin-profile-reactions/runs' \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H 'Content-Type: application/json' \
  -d '{"profiles":["https://www.linkedin.com/in/satyanadella"],"maxItems":5}'

Use the API tab for SDK examples and run/dataset endpoints.

FAQ

Why are there fewer results than a visible counter? Availability, deleted records, filters, source pagination and your run caps can reduce output. Nested reply previews are not separate records.

Can I resume? Run state tracks targets, cursors and delivered IDs. Use the platform's resume/resurrection controls for the same input; start a fresh run when changing input.

Are failed lookups billed as successful records? Successful output rows trigger their configured events. No separate actor-start fee is configured. Review SUMMARY and Pricing for the events used.

Responsible use

Use collected data for a clear purpose, respect privacy and applicable requirements, and retain only the fields your workflow needs.

Support

Open an issue and share the affected run with the developer so we can inspect the error. Never put tokens, cookies or database credentials in a public issue.

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