{
  "data": {
    "id": "5eLObB7fzGGkTtyD3",
    "userId": "HIMU0xktu1JeZb4Xl",
    "name": "linkedin-post-comments-scraper",
    "username": "fetch_cat",
    "description": "Export public LinkedIn post comments and replies with author, thread, engagement, and incremental monitoring fields.",
    "isPublic": true,
    "createdAt": "2026-08-10T14:00:18.458Z",
    "modifiedAt": "2026-08-11T19:38:39.970Z",
    "taggedBuilds": {
      "latest": {
        "buildId": "gouBclng1zhlccqve",
        "finishedAt": "2026-08-10T15:46:27.789Z",
        "buildNumberInt": 100008,
        "buildNumber": "0.1.8"
      }
    },
    "stats": {
      "totalBuilds": 8,
      "totalRuns": 49,
      "totalUsers": 2,
      "totalUsers7Days": 1,
      "totalUsers30Days": 1,
      "totalUsers90Days": 1,
      "lastRunStartedAt": "2026-08-26T20:08:26.784Z",
      "actorReviewCount": 0,
      "actorReviewRating": 0,
      "bookmarkCount": 0,
      "publicActorRunStats30Days": {
        "ABORTED": 0,
        "FAILED": 0,
        "SUCCEEDED": 15,
        "TIMED-OUT": 0,
        "TOTAL": 15
      }
    },
    "versions": [
      {
        "versionNumber": "0.1",
        "sourceType": "SOURCE_FILES",
        "buildTag": "latest"
      }
    ],
    "defaultRunOptions": {
      "build": "latest",
      "timeoutSecs": 300,
      "memoryMbytes": 256
    },
    "exampleRunInput": {
      "body": "{\"postUrls\": [\"https://www.linkedin.com/posts/satyanadella_no-one-becomes-a-clinician-to-do-paperwork-activity-7302346926123798528-jitu\"], \"maxComments\": 5, \"includeReplies\": true, \"maxRepliesPerComment\": 5, \"sortBy\": \"recent\"}",
      "contentType": "application/json"
    },
    "categories": [
      "SOCIAL_MEDIA",
      "MARKETING"
    ],
    "isDeprecated": false,
    "title": "LinkedIn Post Comments Scraper",
    "pictureUrl": "https://apify-image-uploads-prod.s3.us-east-1.amazonaws.com/HIMU0xktu1JeZb4Xl-actor-5eLObB7fzGGkTtyD3-1Rzhk4VExN-actor-icon.png",
    "seoTitle": "LinkedIn Post Comments Scraper – Export Replies",
    "seoDescription": "Export public LinkedIn post comments and replies with author details, timestamps, reactions, thread links, rank, and monitoring fields via API or MCP.",
    "pricingInfos": [
      {
        "pricingModel": "PAY_PER_EVENT",
        "startedAt": "2026-08-10T14:03:58.466Z",
        "reasonForChange": "Pay only for each public comment or reply saved, with lower per-result prices available on higher Apify plans.",
        "pricingPerEvent": {
          "actorChargeEvents": {
            "start": {
              "eventTitle": "Start",
              "eventDescription": "One-time fee per run",
              "eventPriceUsd": 0.005,
              "isOneTimeEvent": true
            },
            "comment": {
              "eventTitle": "Comment or reply exported",
              "eventDescription": "Charged for each public comment or reply saved",
              "isPrimaryEvent": true,
              "eventTieredPricingUsd": {
                "FREE": {
                  "tieredEventPriceUsd": 0.00115
                },
                "BRONZE": {
                  "tieredEventPriceUsd": 0.001
                },
                "SILVER": {
                  "tieredEventPriceUsd": 0.00078
                },
                "GOLD": {
                  "tieredEventPriceUsd": 0.0006
                },
                "PLATINUM": {
                  "tieredEventPriceUsd": 0.0004
                },
                "DIAMOND": {
                  "tieredEventPriceUsd": 0.00028
                }
              }
            }
          }
        },
        "createdAt": "2026-08-10T14:04:07.818Z",
        "apifyMarginPercentage": 0.2
      },
      {
        "pricingModel": "PAY_PER_EVENT",
        "startedAt": "2026-08-10T14:07:52.409Z",
        "reasonForChange": "Per-result prices were reduced, so customers pay less for every public comment or reply saved.",
        "pricingPerEvent": {
          "actorChargeEvents": {
            "start": {
              "eventTitle": "Run started",
              "eventDescription": "One-time fee charged when a run starts. Covers fixed startup cost (init, proxy warmup, first HTTP setup).",
              "eventPriceUsd": 0.005,
              "isOneTimeEvent": true
            },
            "comment": {
              "eventTitle": "Comment or reply exported",
              "eventDescription": "Charged for each public comment or reply saved",
              "eventTieredPricingUsd": {
                "FREE": {
                  "tieredEventPriceUsd": 0.00004561
                },
                "BRONZE": {
                  "tieredEventPriceUsd": 0.000039661
                },
                "SILVER": {
                  "tieredEventPriceUsd": 0.000030936
                },
                "GOLD": {
                  "tieredEventPriceUsd": 0.000023797
                },
                "PLATINUM": {
                  "tieredEventPriceUsd": 0.000015864
                },
                "DIAMOND": {
                  "tieredEventPriceUsd": 0.000011105
                }
              },
              "isPrimaryEvent": true
            }
          }
        },
        "createdAt": "2026-08-10T14:07:52.807Z",
        "apifyMarginPercentage": 0.2
      }
    ],
    "notice": "NONE",
    "isCritical": false,
    "isGeneric": false,
    "hasNoDataset": false,
    "isSourceCodeHidden": true,
    "standbyUrl": null,
    "actorPermissionLevel": "LIMITED_PERMISSIONS",
    "readmeSummary": "## LinkedIn Post Comments Scraper\n\nA LinkedIn comments scraper that extracts public post comments and replies into structured, row-oriented data for analysis and monitoring. It crawls specified public LinkedIn posts (URLs or URNs) and returns one row per comment or reply with stable identifiers, comment text, public author attribution when available, publication timestamps, reaction and reply totals, parent–child linkage for thread relationships, ordering and pagination provenance, and incremental-monitoring metadata. The output is a flat, linked row format suitable for spreadsheets, BI tools, databases, and downstream analysis, with replies represented as separate rows that preserve parent identifiers for relational joins and deduplication.\n\n## Use cases\n\n- Engagement monitoring and discussion archiving for social and community teams  \n- Detecting recruiting signals and assessing public professional discussion for talent teams  \n- Identifying public buying signals and follow-up opportunities for sales teams  \n- Archiving thread structure, engagement metrics, and authorship for researchers and analysts  \n- Feeding structured LinkedIn discussion data into databases, dashboards, and analytics pipelines",
    "deploymentKey": "ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQDk04cgYuZe6zEDEMgoDaYqjZvyBHprKlOPJXZWCosMlEKwqzmH1d+AfV3/tPujZViqHlFboj7x7toIFwSLUvu6ALZ+/QvAGys+vK5ipZfilfXGsGIZQnORHPZFPZdMkH4PhBTAW0/5hMO8HIjFHJm/gGKfBj7S/F0aUS4W0ZwZuM20GyilAUaDI3LKkouBtTDI0tp0qR3urI1xauf5PX0MjbNq3K5vrqbbBs99UbewUirP/JnIGAErqbTxVcncYiHegpSBJPGmC5cURtAgmcXbtWuLCI1wLswdBMdWy2+eSIx2kvXMrir0qQIXRnfKFp0u7IpfdmXHV/CEt1G6Ac7r \n"
  }
}