LinkedIn ghost jobs: how common they are, what they look like in the data, and how to filter them out

LinkedIn is the board people mean when they complain about ghost jobs, partly because it is where they see the most listings and partly because a LinkedIn posting can stay visible for months. This post gives the LinkedIn cut of the JobsPipe ghost score, compares it with all ten boards, explains what makes LinkedIn read the way it does, and shows the filter that removes the stale share.

Are there ghost jobs on LinkedIn?

Yes, at a rate slightly above the cross-board average. 78.8% of scored active LinkedIn postings sit in the 0-24 band, the clean range, against 82.3% across all boards. 21.2% score 25 or higher, roughly 1 in 5 postings, compared with 17.8% overall.

Very few LinkedIn postings reach the 50 or higher band, where several signals stack. The LinkedIn ghost problem is wide and shallow: a lot of postings with one strong signal, very few with three. Age shows the same shape: 31.1% of active LinkedIn postings were first sighted more than 30 days ago, but only 4.0% more than 45 days ago, because most LinkedIn listings leave the board at the end of their 30-day window.

How JobsPipe sights LinkedIn listings

JobsPipe collects LinkedIn’s public guest job listings, the pages anyone can open without signing in, and records a sighting each time a listing is present on a scheduled pass. Closures on LinkedIn are detected when a listing reaches the end of its 30-day window rather than continuously, so a closed LinkedIn record usually carries a closed_at about a month after its first sighting. Each record carries discovered_at for the first sighting, last_seen_at for the last confirmed-live recheck and closed_reason when it closes. The guest view is thinner than the signed-in view, which is why coverage details live on the LinkedIn source page.

LinkedIn ghost job signals compared with all boards

Two rows explain LinkedIn’s position. The mass poster signal, a company with 500 or more open roles at once, sits on 20.2% of scored LinkedIn postings, which is where the bulk of the 25-49 band comes from: LinkedIn is the board where the largest employers and the staffing agencies cross-post everything. And 76.9% of scored LinkedIn postings carry no salary, above the cross-board share, because LinkedIn’s own salary field is optional and often left blank.

The signals that would indicate deliberate placeholders are rare. Only 1.7% of scored LinkedIn postings have a thin description and only 3.0% have been open 45 days or more. The stale posted date signal is almost absent, because LinkedIn dates a listing once and does not re-date it on edit the way some applicant tracking systems do.

Why LinkedIn ghost jobs feel more common than they are

Three things about LinkedIn amplify the experience. Listings can stay open for months unless the poster closes them, so a stale posting stays visible rather than expiring on a timer the way an Indeed free posting does. Cross-posting means the same requisition appears as a LinkedIn job, an ATS job and an aggregator job, so one ghost is seen three times. And the repost share, 9.9% of active LinkedIn postings, is above the cross-board share because reposting is how a listing gets back to the top of the feed.

A fourth factor is the applicant counter. LinkedIn shows how many people have clicked apply, and a posting with hundreds of applicants and no visible outcome feels like a ghost whether or not it is one. The counter measures interest, not the state of the requisition, and it says nothing about whether anyone is reading the applications.

None of that makes the typical LinkedIn posting a ghost. It makes the typical stale LinkedIn posting more visible than a stale posting elsewhere. The by-board comparison on the LinkedIn ghost jobs page puts LinkedIn next to the boards that actually top the table.

What a LinkedIn ghost job looks like on the record

The clearest way to see the difference between a live LinkedIn posting and a ghost-like one is to put the two records side by side. A live posting has a discovered_at a few days after its date_posted, a last_seen_at that keeps moving forward on each recheck, a ghost_score in the 0-24 band, and, a few weeks later, a closed_at with a closed_reason of closed when the listing reports it is no longer accepting applications, or gone when the page disappears.

A ghost-like LinkedIn posting usually fails on one of three patterns. The first is the evergreen requisition at a mass poster: the posting belongs to a company with hundreds of active records, its discovered_at is well past the 45-day line, and it never closes while the company’s other roles do. The second is the agency repost: the same title and text reappear under the same identifier after a gap of ten days or more, three or more times, and each reappearance carries a fresh date_posted. The third is the placeholder: a short description, no salary, and a company you cannot find hiring anywhere else. The first two are common on LinkedIn; the third is rare, and it is the only one that reads as deliberate.

The score bands make the same point in aggregate. Compared with all boards, LinkedIn has a slightly smaller clean band and a slightly larger 25-49 band, and almost nothing above that.

Should you skip LinkedIn postings that score 25-49?

Not automatically. On LinkedIn the 25-49 band is mostly mass poster inventory: real requisitions at very large employers and staffing agencies, where the specific listing may or may not map to a vacancy. Skip the band if you are building a feed for people who want a reply within a week. Keep it, dated by first sighting, if you are sourcing or tracking where large employers are hiring, because those postings are the signal you came for. The band above 50, where age and reposts stack on top of mass posting, is the one to drop in both cases, and on LinkedIn it is tiny.

How to filter LinkedIn ghost jobs with the API

Restrict to LinkedIn with source_or, keep active postings, and cap the score.

curl -X POST https://api.jobspipe.dev/v1/jobs/search \
  -H "Authorization: Bearer $JOBSPIPE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{ "source_or": ["linkedin"], "job_title_or": ["product manager"], "status": "active", "max_ghost_score": 24, "posted_at_max_age_days": 30, "limit": 25 }'

Because the mass poster signal drives most of LinkedIn’s 25-49 band, a cap of 24 will also drop legitimate roles at very large employers. If those matter to you, raise the cap to 44 and rely on posted_at_max_age_days to handle age, or use max_employee_count to scope the search to the company sizes you want. The definitions behind every signal are in what are ghost jobs.