
LinkedIn Profile Engagement Scraper (Company and Profile)
Pricing
$30.00/month + usage

LinkedIn Profile Engagement Scraper (Company and Profile)
A powerful Apify actor to extract post-engagement metrics from LinkedIn profiles. Gather likes, comments, reposts, and more for data-driven insights. Boost your social media strategy today!
0.0 (0)
Pricing
$30.00/month + usage
1
Monthly users
11
Runs succeeded
62%
Response time
1.9 hours
Last modified
16 days ago
You can access the LinkedIn Profile Engagement Scraper (Company and Profile) programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.
1{
2 "openapi": "3.0.1",
3 "info": {
4 "version": "1.0",
5 "x-build-id": "X6DLwEnJ9KWUPiRiB"
6 },
7 "servers": [
8 {
9 "url": "https://api.apify.com/v2"
10 }
11 ],
12 "paths": {
13 "/acts/ahmed-khaled~linkedin-engagement-scraper/run-sync-get-dataset-items": {
14 "post": {
15 "operationId": "run-sync-get-dataset-items-ahmed-khaled-linkedin-engagement-scraper",
16 "x-openai-isConsequential": false,
17 "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
18 "tags": [
19 "Run Actor"
20 ],
21 "requestBody": {
22 "required": true,
23 "content": {
24 "application/json": {
25 "schema": {
26 "$ref": "#/components/schemas/inputSchema"
27 }
28 }
29 }
30 },
31 "parameters": [
32 {
33 "name": "token",
34 "in": "query",
35 "required": true,
36 "schema": {
37 "type": "string"
38 },
39 "description": "Enter your Apify token here"
40 }
41 ],
42 "responses": {
43 "200": {
44 "description": "OK"
45 }
46 }
47 }
48 },
49 "/acts/ahmed-khaled~linkedin-engagement-scraper/runs": {
50 "post": {
51 "operationId": "runs-sync-ahmed-khaled-linkedin-engagement-scraper",
52 "x-openai-isConsequential": false,
53 "summary": "Executes an Actor and returns information about the initiated run in response.",
54 "tags": [
55 "Run Actor"
56 ],
57 "requestBody": {
58 "required": true,
59 "content": {
60 "application/json": {
61 "schema": {
62 "$ref": "#/components/schemas/inputSchema"
63 }
64 }
65 }
66 },
67 "parameters": [
68 {
69 "name": "token",
70 "in": "query",
71 "required": true,
72 "schema": {
73 "type": "string"
74 },
75 "description": "Enter your Apify token here"
76 }
77 ],
78 "responses": {
79 "200": {
80 "description": "OK",
81 "content": {
82 "application/json": {
83 "schema": {
84 "$ref": "#/components/schemas/runsResponseSchema"
85 }
86 }
87 }
88 }
89 }
90 }
91 },
92 "/acts/ahmed-khaled~linkedin-engagement-scraper/run-sync": {
93 "post": {
94 "operationId": "run-sync-ahmed-khaled-linkedin-engagement-scraper",
95 "x-openai-isConsequential": false,
96 "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
97 "tags": [
98 "Run Actor"
99 ],
100 "requestBody": {
101 "required": true,
102 "content": {
103 "application/json": {
104 "schema": {
105 "$ref": "#/components/schemas/inputSchema"
106 }
107 }
108 }
109 },
110 "parameters": [
111 {
112 "name": "token",
113 "in": "query",
114 "required": true,
115 "schema": {
116 "type": "string"
117 },
118 "description": "Enter your Apify token here"
119 }
120 ],
121 "responses": {
122 "200": {
123 "description": "OK"
124 }
125 }
126 }
127 }
128 },
129 "components": {
130 "schemas": {
131 "inputSchema": {
132 "type": "object",
133 "required": [
134 "url",
135 "cookie"
136 ],
137 "properties": {
138 "url": {
139 "title": "URL of the Linkedin profile",
140 "type": "string",
141 "description": "The URL of Linkedin profile you want to get the data from."
142 },
143 "cookie": {
144 "title": "The Cookie",
145 "type": "string",
146 "description": "Cookie used to authorize actor with linkedin.com. Install [EditThisCookie](https://chrome.google.com/webstore/detail/editthiscookie/fngmhnnpilhplaeedifhccceomclgfbg) chrome extension. Login to your linkedin.com account. Click on the extension and export the linkedin.com cookies. Insert the contents here"
147 },
148 "limit": {
149 "title": "Limit",
150 "type": "integer",
151 "description": "Limit the number of scrolls to scrape, approximately one scroll is about two posts."
152 }
153 }
154 },
155 "runsResponseSchema": {
156 "type": "object",
157 "properties": {
158 "data": {
159 "type": "object",
160 "properties": {
161 "id": {
162 "type": "string"
163 },
164 "actId": {
165 "type": "string"
166 },
167 "userId": {
168 "type": "string"
169 },
170 "startedAt": {
171 "type": "string",
172 "format": "date-time",
173 "example": "2025-01-08T00:00:00.000Z"
174 },
175 "finishedAt": {
176 "type": "string",
177 "format": "date-time",
178 "example": "2025-01-08T00:00:00.000Z"
179 },
180 "status": {
181 "type": "string",
182 "example": "READY"
183 },
184 "meta": {
185 "type": "object",
186 "properties": {
187 "origin": {
188 "type": "string",
189 "example": "API"
190 },
191 "userAgent": {
192 "type": "string"
193 }
194 }
195 },
196 "stats": {
197 "type": "object",
198 "properties": {
199 "inputBodyLen": {
200 "type": "integer",
201 "example": 2000
202 },
203 "rebootCount": {
204 "type": "integer",
205 "example": 0
206 },
207 "restartCount": {
208 "type": "integer",
209 "example": 0
210 },
211 "resurrectCount": {
212 "type": "integer",
213 "example": 0
214 },
215 "computeUnits": {
216 "type": "integer",
217 "example": 0
218 }
219 }
220 },
221 "options": {
222 "type": "object",
223 "properties": {
224 "build": {
225 "type": "string",
226 "example": "latest"
227 },
228 "timeoutSecs": {
229 "type": "integer",
230 "example": 300
231 },
232 "memoryMbytes": {
233 "type": "integer",
234 "example": 1024
235 },
236 "diskMbytes": {
237 "type": "integer",
238 "example": 2048
239 }
240 }
241 },
242 "buildId": {
243 "type": "string"
244 },
245 "defaultKeyValueStoreId": {
246 "type": "string"
247 },
248 "defaultDatasetId": {
249 "type": "string"
250 },
251 "defaultRequestQueueId": {
252 "type": "string"
253 },
254 "buildNumber": {
255 "type": "string",
256 "example": "1.0.0"
257 },
258 "containerUrl": {
259 "type": "string"
260 },
261 "usage": {
262 "type": "object",
263 "properties": {
264 "ACTOR_COMPUTE_UNITS": {
265 "type": "integer",
266 "example": 0
267 },
268 "DATASET_READS": {
269 "type": "integer",
270 "example": 0
271 },
272 "DATASET_WRITES": {
273 "type": "integer",
274 "example": 0
275 },
276 "KEY_VALUE_STORE_READS": {
277 "type": "integer",
278 "example": 0
279 },
280 "KEY_VALUE_STORE_WRITES": {
281 "type": "integer",
282 "example": 1
283 },
284 "KEY_VALUE_STORE_LISTS": {
285 "type": "integer",
286 "example": 0
287 },
288 "REQUEST_QUEUE_READS": {
289 "type": "integer",
290 "example": 0
291 },
292 "REQUEST_QUEUE_WRITES": {
293 "type": "integer",
294 "example": 0
295 },
296 "DATA_TRANSFER_INTERNAL_GBYTES": {
297 "type": "integer",
298 "example": 0
299 },
300 "DATA_TRANSFER_EXTERNAL_GBYTES": {
301 "type": "integer",
302 "example": 0
303 },
304 "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
305 "type": "integer",
306 "example": 0
307 },
308 "PROXY_SERPS": {
309 "type": "integer",
310 "example": 0
311 }
312 }
313 },
314 "usageTotalUsd": {
315 "type": "number",
316 "example": 0.00005
317 },
318 "usageUsd": {
319 "type": "object",
320 "properties": {
321 "ACTOR_COMPUTE_UNITS": {
322 "type": "integer",
323 "example": 0
324 },
325 "DATASET_READS": {
326 "type": "integer",
327 "example": 0
328 },
329 "DATASET_WRITES": {
330 "type": "integer",
331 "example": 0
332 },
333 "KEY_VALUE_STORE_READS": {
334 "type": "integer",
335 "example": 0
336 },
337 "KEY_VALUE_STORE_WRITES": {
338 "type": "number",
339 "example": 0.00005
340 },
341 "KEY_VALUE_STORE_LISTS": {
342 "type": "integer",
343 "example": 0
344 },
345 "REQUEST_QUEUE_READS": {
346 "type": "integer",
347 "example": 0
348 },
349 "REQUEST_QUEUE_WRITES": {
350 "type": "integer",
351 "example": 0
352 },
353 "DATA_TRANSFER_INTERNAL_GBYTES": {
354 "type": "integer",
355 "example": 0
356 },
357 "DATA_TRANSFER_EXTERNAL_GBYTES": {
358 "type": "integer",
359 "example": 0
360 },
361 "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
362 "type": "integer",
363 "example": 0
364 },
365 "PROXY_SERPS": {
366 "type": "integer",
367 "example": 0
368 }
369 }
370 }
371 }
372 }
373 }
374 }
375 }
376 }
377}
LinkedIn Profile Engagement Scraper (Company and Profile) OpenAPI definition
OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.
OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.
By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.
You can download the OpenAPI definitions for LinkedIn Profile Engagement Scraper (Company and Profile) from the options below:
If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.
You can also check out our other API clients:
Pricing
Pricing model
RentalTo use this Actor, you have to pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period. You also pay for the Apify platform usage.
Free trial
14 days
Price
$30.00